Analogy-Related Information Can Be Accessed by Simple Addition and Subtraction of fMRI Activation Patterns, Without Participants Performing any Analogy Task.

Analogical reasoning, for example, inferring that is to as is to , plays a fundamental role in human cognition. However, whether brain activity patterns of individual words are encoded in a way that could facilitate analogical reasoning is unclear. Recent advances in computational linguistics have shown that information about analogical problems can be accessed by simple addition and subtraction of word embeddings (e.

Cortical Transformation of Stimulus Space in Order to Linearize a Linearly Inseparable Task.

The human brain is able to learn difficult categorization tasks, even ones that have linearly inseparable boundaries; however, it is currently unknown how it achieves this computational feat. We investigated this by training participants on an animal categorization task with a linearly inseparable prototype structure in a morph shape space. Participants underwent fMRI scans before and after 4 days of behavioral training.

An Integrated Neural Decoder of Linguistic and Experiential Meaning.

The brain is thought to combine linguistic knowledge of words and nonlinguistic knowledge of their referents to encode sentence meaning. However, functional neuroimaging studies aiming at decoding language meaning from neural activity have mostly relied on distributional models of word semantics, which are based on patterns of word co-occurrence in text corpora. Here, we present initial evidence that modeling nonlinguistic "experiential" knowledge contributes to decoding neural representations of sentence meaning.

Multiple Regions of a Cortical Network Commonly Encode the Meaning of Words in Multiple Grammatical Positions of Read Sentences.

Deciphering how sentence meaning is represented in the brain remains a major challenge to science. Semantically related neural activity has recently been shown to arise concurrently in distributed brain regions as successive words in a sentence are read. However, what semantic content is represented by different regions, what is common across them, and how this relates to words in different grammatical positions of sentences is weakly understood.

Longitudinal Functional Brain Mapping in Supernormals.

Prevention of age-related cognitive decline is an increasingly important topic. Recently, increased attention is being directed at understanding biological models of successful cognitive aging. Here, we examined resting-state brain regional low-frequency oscillations using functional magnetic resonance imaging in 19 older adults with excellent cognitive abilities (Supernormals), 28 older adults with normative cognition, 57 older adults with amnestic mild cognitive impairment, and 26 with Alzheimer's disease.

Identify a shared neural circuit linking multiple neuropsychiatric symptoms with Alzheimer's pathology.

Neuropsychiatric symptoms (NPS) are common in Alzheimer's disease (AD)-associated neurodegeneration. However, NPS lack a consistent relationship with AD pathology. It is unknown whether any common neural circuits can link these clinically disparate while mechanistically similar features with AD pathology.

Decoding semantic representations from functional near-infrared spectroscopy signals.

This study uses representational similarity-based neural decoding to test whether semantic information elicited by words and pictures is encoded in functional near-infrared spectroscopy (fNIRS) data. In experiment 1, subjects passively viewed eight audiovisual word and picture stimuli for 15 min. Blood oxygen levels were measured using the Hitachi ETG-4000 fNIRS system with a posterior array over the occipital lobe and a left lateral array over the temporal lobe.

Decoding the infant mind: Multivariate pattern analysis (MVPA) using fNIRS.

The MRI environment restricts the types of populations and tasks that can be studied by cognitive neuroscientists (e.g., young infants, face-to-face communication).

Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation.

Semantic Structural Alignment of Neural Representational Spaces Enables Translation between English and Chinese Words.

Two sets of items can share the same underlying conceptual structure, while appearing unrelated at a surface level. Humans excel at recognizing and using alignments between such underlying structures in many domains of cognition, most notably in analogical reasoning. Here we show that structural alignment reveals how different people's neural representations of word meaning are preserved across different languages, such that patterns of brain activation can be used to translate words from one language to another.

Representational similarity encoding for fMRI: Pattern-based synthesis to predict brain activity using stimulus-model-similarities.

Patterns of neural activity are systematically elicited as the brain experiences categorical stimuli and a major challenge is to understand what these patterns represent. Two influential approaches, hitherto treated as separate analyses, have targeted this problem by using model-representations of stimuli to interpret the corresponding neural activity patterns. Stimulus-model-based-encoding synthesizes neural activity patterns by first training weights to map between stimulus-model features and voxels.

A high-efficiency fiber-based imaging system for co-registered autofluorescence and optical coherence tomography.

We present a power-efficient fiber-based imaging system capable of co-registered autofluorescence imaging and optical coherence tomography (AF/OCT). The system employs a custom fiber optic rotary joint (FORJ) with an embedded dichroic mirror to efficiently combine the OCT and AF pathways. This three-port wavelength multiplexing FORJ setup has a throughput of more than 83% for collected AF emission, significantly more efficient compared to previously reported fiber-based methods.

Smoothness without smoothing: why Gaussian naive Bayes is not naive for multi-subject searchlight studies.

Spatial smoothness is helpful when averaging fMRI signals across multiple subjects, as it allows different subjects' corresponding brain areas to be pooled together even if they are slightly misaligned. However, smoothing is usually not applied when performing multivoxel pattern-based analyses (MVPA), as it runs the risk of blurring away the information that fine-grained spatial patterns contain. It would therefore be desirable, if possible, to carry out pattern-based analyses which take unsmoothed data as their input but which produce smooth images as output.

Categorical speech processing in Broca's area: an fMRI study using multivariate pattern-based analysis.

Although much effort has been directed toward understanding the neural basis of speech processing, the neural processes involved in the categorical perception of speech have been relatively less studied, and many questions remain open. In this functional magnetic resonance imaging (fMRI) study, we probed the cortical regions mediating categorical speech perception using an advanced brain-mapping technique, whole-brain multivariate pattern-based analysis (MVPA). Normal healthy human subjects (native English speakers) were scanned while they listened to 10 consonant-vowel syllables along the /ba/-/da/ continuum.

What makes different people's representations alike: neural similarity space solves the problem of across-subject fMRI decoding.

A central goal in neuroscience is to interpret neural activation and, moreover, to do so in a way that captures universal principles by generalizing across individuals. Recent research in multivoxel pattern-based fMRI analysis has led to considerable success at decoding within individual subjects. However, the goal of being able to decode across subjects is still challenging: It has remained unclear what population-level regularities of neural representation there might be.

Level of organochlorine pesticide residues in dry fruit nuts.

The use of pesticides on cash crops and exportable food commodities had always been a serious concern. Fruits form one of the important constituents of human diet, in that they give one third of the requirement of calories, vitamins, and minerals. This study has been carried out to determine the level of organochlorine pesticides namely HCH, DDT and Endosulfan in raw fruit nuts.

Assessment of chlorpyrifos toxicity on certain organs in rat, Rattus norvegicus.

Chlorpyrifos, an organophosphate insecticide of phosphorothioate group was orally administered to male rats at the doses of 3, 6 and 9 mg kg(-1) d(-1) for 90 days. Animals exposed to high dose (9 mg kg(-1) d(-1)) showed signs of toxicity including piloerection, diarrhoea, nose and eye bleeding, reduced body weight and death of animals. Organ weight ratio of different vital organs did not show any change except increase in adrenal weight and decrease in the weight of testes in animals of high dose (9 mg kg(-1) d(-1)).

Effects of socioeconomic status on brain development, and how cognitive neuroscience may contribute to levelling the playing field.

THE STUDY OF SOCIOECONOMIC STATUS (SES) AND THE BRAIN FINDS ITSELF IN A CIRCUMSTANCE UNUSUAL FOR COGNITIVE NEUROSCIENCE: large numbers of questions with both practical and scientific importance exist, but they are currently under-researched and ripe for investigation. This review aims to highlight these questions, to outline their potential significance, and to suggest routes by which they might be approached. Although remarkably few neural studies have been carried out so far, there exists a large literature of previous behavioural work.

Evaluation of comparative effect of pre- and posttreatment of selenium on mercury-induced oxidative stress, histological alterations, and metallothionein mRNA expression in rats.

To evaluate the effect of pre- or posttreatment of selenium (6 micromol/kg b.w., single intraperitoneal injection) in mercury intoxication, rats were exposed to mercury (12 micromol/kg b.

Linking brain-wide multivoxel activation patterns to behaviour: Examples from language and math.

A key goal of cognitive neuroscience is to find simple and direct connections between brain and behaviour. However, fMRI analysis typically involves choices between many possible options, with each choice potentially biasing any brain-behaviour correlations that emerge. Standard methods of fMRI analysis assess each voxel individually, but then face the problem of selection bias when combining those voxels into a region-of-interest, or ROI.

Quantifying the adequacy of neural representations for a cross-language phonetic discrimination task: prediction of individual differences.

In order for stimuli to be perceptually discriminable, their representations in the brain must be distinct. Investigating the task of discriminating the syllables /ra/ and /la/, we hypothesized that the more distinct a person's neural representations of those sounds were, the better their behavioral ability to discriminate them would be. Standard neuroimaging approaches are ill-suited to testing this hypothesis as they have problems differentiating between neural representations spatially intermingled within the same brain area.

Challenge-driven attention: interacting frontal and brainstem systems.

The world is an unpredictable place, presenting challenges that fluctuate from moment to moment. However, the neural systems for responding to such challenges are far from fully understood. Using fMRI, we studied an audiovisual task in which the trials' difficulty and onset times varied unpredictably.

Socioeconomic status predicts hemispheric specialisation of the left inferior frontal gyrus in young children.

Reading is a complex skill that is not mastered by all children. At the age of 5, on the cusp of prereading development, many factors combine to influence a child's future reading success, including neural and behavioural factors such as phonological awareness and the auditory processing of phonetic input, and environmental factors, such as socioeconomic status (SES). We investigated the interactions between these factors in 5-year-old children by administering a battery of standardised cognitive and linguistic tests, measuring SES with a standardised scale, and using fMRI to record neural activity during a behavioral task, rhyming, that is predictive of reading skills.