scholarly journals The brain of the beholder: honouring individual representational idiosyncrasies

2015 ◽  
Author(s):  
Ian Charest ◽  
Nikolaus Kriegeskorte
Keyword(s):  
Brain Function ◽  
Computational Models ◽  
Stimulus Space ◽  
New Paradigm ◽  
Unique Pattern ◽  
Behavioural Responses ◽  
Population Codes ◽  
Recent Developments ◽  
Multivariate Pattern ◽  
The Brain

In the early days of neuroimaging, brain function was investigated by averaging across voxels within a region, stimuli within a category, and individuals within a group. These three forms of averaging discard important neuroscientific information. Recent studies have explored analyses that combine the evidence in better-motivated ways. Multivariate pattern analyses enable researchers to reveal representations in distributed population codes, honouring the unique information contributed by different voxels (or neurons). Condition-rich designs more richly sample the stimulus space and can treat each stimulus as a unique entity. Finally, each individual’s brain is unique and recent studies have found ways to model and analyse the interindividual representational variability. Here we review our field’s journey towards more sophisticated analyses that honour these important idiosyncrasies of brain representations. We describe an emerging framework for investigating individually unique pattern representations of particular stimuli in the brain. The framework models stimuli, responses and individuals multivariately and relates representations by means of representational dissimilarity matrices. Important components are computational models and multivariate descriptions of brain and behavioural responses. These recent developments promise a new paradigm for studying the individually unique brain at unprecedented levels of representational detail.

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

2020 ◽  
Author(s):  
Sreejan Kumar ◽  
Cameron T. Ellis ◽  
Thomas O’Connell ◽  
Marvin M Chun ◽  
Nicholas B. Turk-Browne
Keyword(s):  
Human Brain ◽  
Language Processing ◽  
Brain Function ◽  
Computational Models ◽  
Brain Activity ◽  
Functional Space ◽  
Semantic Features ◽  
Brain Functions ◽  
Auditory Features ◽  
The Brain

AbstractThe 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 are more widely distributed across the brain than previously acknowledged. 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.

Finding the Brain in the Nose

2020 ◽  
Vol 43 (1) ◽  
pp. 277-295
Author(s):  
David H. Brann ◽  
Sandeep Robert Datta
Keyword(s):  
Brain Function ◽  
Perception And Action ◽  
Complex Mixtures ◽  
Peripheral Population ◽  
Volatile Chemicals ◽  
Sensory Modalities ◽  
Population Codes ◽  
Receptor Array ◽  
Olfactory Stimuli ◽  
The Brain

Olfaction is fundamentally distinct from other sensory modalities. Natural odor stimuli are complex mixtures of volatile chemicals that interact in the nose with a receptor array that, in rodents, is built from more than 1,000 unique receptors. These interactions dictate a peripheral olfactory code, which in the brain is transformed and reformatted as it is broadcast across a set of highly interconnected olfactory regions. Here we discuss the problems of characterizing peripheral population codes for olfactory stimuli, of inferring the specific functions of different higher olfactory areas given their extensive recurrence, and of ultimately understanding how odor representations are linked to perception and action. We argue that, despite the differences between olfaction and other sensory modalities, addressing these specific questions will reveal general principles underlying brain function.

Reason for optimism: How a shifting focus on neural population codes is moving cognitive neuroscience beyond phrenology

2016 ◽  
Vol 39 ◽  
Author(s):  
Carolyn Parkinson ◽  
Thalia Wheatley
Keyword(s):  
Cognitive Neuroscience ◽  
Brain Function ◽  
Pattern Analysis ◽  
Brain Regions ◽  
Neural Population ◽  
Multivariate Pattern Analysis ◽  
Population Responses ◽  
Population Codes ◽  
Multivariate Pattern ◽  
Insight Into

AbstractMultivariate pattern analysis can address many of the challenges for cognitive neuroscience highlighted in After Phrenology (Anderson 2014) by illuminating the information content of brain regions and by providing insight into whether functional overlap reflects the recruitment of common or distinct computational mechanisms. Further, failing to consider submaximal but reliable population responses can lead to an overly modular account of brain function.

scholarly journals The neural architecture of language: Integrative reverse-engineering converges on a model for predictive processing

2020 ◽  
Author(s):  
Martin Schrimpf ◽  
Idan Blank ◽  
Greta Tuckute ◽  
Carina Kauf ◽  
Eghbal A. Hosseini ◽  
...  
Keyword(s):  
Reverse Engineering ◽  
Language Processing ◽  
Brain Function ◽  
Computational Models ◽  
Predictive Processing ◽  
Neural Responses ◽  
Data Types ◽  
Neural Architecture ◽  
And Behavior ◽  
The Brain

AbstractThe neuroscience of perception has recently been revolutionized with an integrative reverse-engineering approach in which computation, brain function, and behavior are linked across many different datasets and many computational models. We here present a first systematic study taking this approach into higher-level cognition: human language processing, our species’ signature cognitive skill. We find that the most powerful ‘transformer’ networks predict neural responses at nearly 100% and generalize across different datasets and data types (fMRI, ECoG). Across models, significant correlations are observed among all three metrics of performance: neural fit, fit to behavioral responses, and accuracy on the next-word prediction task (but not other language tasks), consistent with the long-standing hypothesis that the brain’s language system is optimized for predictive processing. Model architectures with initial weights further perform surprisingly similar to final trained models, suggesting that inherent structure – and not just experience with language – crucially contributes to a model’s match to the brain.

Fuzzy-based computational simulations of brain functions – preliminary concept

2016 ◽  
Vol 12 (3) ◽  
Author(s):  
Piotr Prokopowicz ◽  
Dariusz Mikołajewski
Keyword(s):  
Applied Sciences ◽  
Fuzzy Logic ◽  
Computational Neuroscience ◽  
Brain Function ◽  
Computational Models ◽  
Fuzzy Numbers ◽  
Brain Functions ◽  
Current State ◽  
Simulation Based ◽  
The Brain

AbstractResearch on the computational models of the brain constitutes an important part of the current challenges within computational neuroscience. The current results are not satisfying. Despite the continuous efforts of scientists and clinicians, it is hard to fully explain all the mechanisms of a brain function. Computational models of the brain based on fuzzy logic, including ordered fuzzy numbers, may constitute another breakthrough in the aforementioned area, offering a completing position to the current state of the art. The aim of this paper is to assess the extent to which possible opportunities concerning computational brain models based on fuzzy logic techniques may be exploited both in the area of theoretical and experimental computational neuroscience and in clinical applications, including our own concept. The proposed approach can open a family of novel methods for a more effective and (neuro)biologically reliable brain simulation based on fuzzy logic techniques useful in both basic sciences and applied sciences.

scholarly journals PhenoWorld: addressing animal welfare in a new paradigm to house and assess rat behaviour

2016 ◽  
Vol 51 (1) ◽  
pp. 36-43 ◽  
Author(s):  
Magda J Castelhano-Carlos ◽  
Vera Baumans ◽  
Nuno Sousa
Keyword(s):  
Animal Welfare ◽  
Brain Function ◽  
Animal Experiments ◽  
Well Being ◽  
Housing Conditions ◽  
Affective States ◽  
New Paradigm ◽  
Social Challenges ◽  
International Regulations ◽  
The Brain

The use of animals is essential in biomedical research. The laboratory environment where the animals are housed has a major impact on them throughout their lives and influences the outcome of animal experiments. Therefore, there has been an increased effort in the refinement of laboratory housing conditions which is explicitly reflected in international regulations and recommendations. Since housing conditions affect behaviour and brain function as well as well-being, the validation of an animal model or paradigm to study the brain and central nervous system disorders is not complete without an evaluation of its implication on animal welfare. Here we discuss several aspects of animal welfare, comparing groups of six rats living in the PhenoWorld (PhW), a recently developed and validated paradigm for studying rodent behaviour, with standard-housed animals (in cages of six rats or pair-housed). In this study we present new data on home-cage behaviour showing that PhW animals have a clearer circadian pattern of sleep and social interaction. We conclude that, by promoting good basic health and functioning, together with the performance of natural behaviours, and maintaining animals’ control over some of their environment but still keeping some physical and social challenges, the PhW stimulates positive affective states and higher motivation in rats, which might contribute to an increased welfare for animals living in the PhW.

Frontier concept of rabi chip for intelligent humanoid

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Preecha Yupapin ◽  
Amiri I. S. ◽  
Ali J. ◽  
Ponsuwancharoen N. ◽  
Youplao P.
Keyword(s):  
Human Brain ◽  
Brain Function ◽  
Rabi Oscillation ◽  
Liquid Core ◽  
Brain Surface ◽  
Dipole Oscillation ◽  
On Chip ◽  
The Brain ◽  
Robotic Applications ◽  
Atom System

The sequence of the human brain can be configured by the originated strongly coupling fields to a pair of the ionic substances(bio-cells) within the microtubules. From which the dipole oscillation begins and transports by the strong trapped force, which is known as a tweezer. The tweezers are the trapped polaritons, which are the electrical charges with information. They will be collected on the brain surface and transport via the liquid core guide wave, which is the mixture of blood content and water. The oscillation frequency is called the Rabi frequency, is formed by the two-level atom system. Our aim will manipulate the Rabi oscillation by an on-chip device, where the quantum outputs may help to form the realistic human brain function for humanoid robotic applications.

Finding Community of Brain Networks Based on Neighbor Index and DPSO with Dynamic Crossover

2020 ◽  
Vol 15 (4) ◽  
pp. 287-299
Author(s):  
Jie Zhang ◽  
Junhong Feng ◽  
Fang-Xiang Wu
Keyword(s):  
Brain Function ◽  
Brain Networks ◽  
Discrete Particle Swarm Optimization ◽  
Mri Brain ◽  
Mutation Operators ◽  
Neural Unit ◽  
Crossover And Mutation ◽  
The Brain ◽  
Index Table ◽  
Dynamic Crossover

Background: : The brain networks can provide us an effective way to analyze brain function and brain disease detection. In brain networks, there exist some import neural unit modules, which contain meaningful biological insights. Objective:: Therefore, we need to find the optimal neural unit modules effectively and efficiently. Method:: In this study, we propose a novel algorithm to find community modules of brain networks by combining Neighbor Index and Discrete Particle Swarm Optimization (DPSO) with dynamic crossover, abbreviated as NIDPSO. The differences between this study and the existing ones lie in that NIDPSO is proposed first to find community modules of brain networks, and dose not need to predefine and preestimate the number of communities in advance. Results: : We generate a neighbor index table to alleviate and eliminate ineffective searches and design a novel coding by which we can determine the community without computing the distances amongst vertices in brain networks. Furthermore, dynamic crossover and mutation operators are designed to modify NIDPSO so as to alleviate the drawback of premature convergence in DPSO. Conclusion: The numerical results performing on several resting-state functional MRI brain networks demonstrate that NIDPSO outperforms or is comparable with other competing methods in terms of modularity, coverage and conductance metrics.

Neuroethics

2017 ◽  
Keyword(s):  
Brain Function ◽  
Ethical Issues ◽  
Wearable Technologies ◽  
Definition Of Death ◽  
Populations At Risk ◽  
The Future ◽  
Aging Adults ◽  
Definition Of ◽  
The Brain ◽  
New Criteria

We have new answers to how the brain works and tools which can now monitor and manipulate brain function. Rapid advances in neuroscience raise critical questions with which society must grapple. What new balances must be struck between diagnosis and prediction, and invasive and noninvasive interventions? Are new criteria needed for the clinical definition of death in cases where individuals are eligible for organ donation? How will new mobile and wearable technologies affect the future of growing children and aging adults? To what extent is society responsible for protecting populations at risk from environmental neurotoxins? As data from emerging technologies converge and are made available on public databases, what frameworks and policies will maximize benefits while ensuring privacy of health information? And how can people and communities with different values and perspectives be maximally engaged in these important questions? Neuroethics: Anticipating the Future is written by scholars from diverse disciplines—neurology and neuroscience, ethics and law, public health, sociology, and philosophy. With its forward-looking insights and considerations for the future, the book examines the most pressing current ethical issues.

Implantable neural interfaces

2018 ◽  
Author(s):  
Stefano Vassanelli
Keyword(s):  
Brain Function ◽  
Large Scale ◽  
Ionic Channels ◽  
Patch Clamp Technique ◽  
Advantages And Disadvantages ◽  
Optogenetic Stimulation ◽  
Physical Interfaces ◽  
The Brain

Establishing direct communication with the brain through physical interfaces is a fundamental strategy to investigate brain function. Starting with the patch-clamp technique in the seventies, neuroscience has moved from detailed characterization of ionic channels to the analysis of single neurons and, more recently, microcircuits in brain neuronal networks. Development of new biohybrid probes with electrodes for recording and stimulating neurons in the living animal is a natural consequence of this trend. The recent introduction of optogenetic stimulation and advanced high-resolution large-scale electrical recording approaches demonstrates this need. Brain implants for real-time neurophysiology are also opening new avenues for neuroprosthetics to restore brain function after injury or in neurological disorders. This chapter provides an overview on existing and emergent neurophysiology technologies with particular focus on those intended to interface neuronal microcircuits in vivo. Chemical, electrical, and optogenetic-based interfaces are presented, with an analysis of advantages and disadvantages of the different technical approaches.

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