scholarly journals Abstract Neural Representations of Category Membership beyond Information Coding Stimulus or Response

2020 ◽  
pp. 1-17
Author(s):  
Robert M. Mok ◽  
Bradley C. Love
Keyword(s):  
Mental Representations ◽  
Cognitive Model ◽  
Brain Regions ◽  
Information Coding ◽  
Abstract Representation ◽  
Motor Programs ◽  
Sensory Inputs ◽  
Sensory Motor ◽  
Concept Representations ◽  
The Brain

For decades, researchers have debated whether mental representations are symbolic or grounded in sensory inputs and motor programs. Certainly, aspects of mental representations are grounded. However, does the brain also contain abstract concept representations that mediate between perception and action in a flexible manner not tied to the details of sensory inputs and motor programs? Such conceptual pointers would be useful when concepts remain constant despite changes in appearance and associated actions. We evaluated whether human participants acquire such representations using fMRI. Participants completed a probabilistic concept learning task in which sensory, motor, and category variables were not perfectly coupled or entirely independent, making it possible to observe evidence for abstract representations or purely grounded representations. To assess how the learned concept structure is represented in the brain, we examined brain regions implicated in flexible cognition (e.g., pFC and parietal cortex) that are most likely to encode an abstract representation removed from sensory–motor details. We also examined sensory–motor regions that might encode grounded sensory–motor-based representations tuned for categorization. Using a cognitive model to estimate participants' category rule and multivariate pattern analysis of fMRI data, we found the left pFC and MT coded for category in the absence of information coding for stimulus or response. Because category was based on the stimulus, finding an abstract representation of category was not inevitable. Our results suggest that certain brain areas support categorization behavior by constructing concept representations in a format akin to a symbol that differs from stimulus–motor codes.

scholarly journals Abstract neural representations of category membership beyond information coding stimulus or response

2020 ◽  
Author(s):  
Robert M. Mok ◽  
Bradley C. Love
Keyword(s):  
Mental Representations ◽  
Cognitive Model ◽  
Brain Regions ◽  
Information Coding ◽  
Abstract Representation ◽  
Motor Programs ◽  
Sensory Inputs ◽  
Sensory Motor ◽  
Concept Representations ◽  
The Brain

AbstractFor decades, researchers have debated whether mental representations are symbolic or grounded in sensory inputs and motor programs. Certainly, aspects of mental representations are grounded. However, does the brain also contain abstract concept representations that mediate between perception and action in a flexible manner not tied to the details of sensory inputs and motor programs? Such conceptual pointers would be useful when concept remain constant despite changes in appearance and associated actions. We evaluated whether human participants acquire such representations using functional magnetic resonance imaging (fMRI). Participants completed a probabilistic concept learning task in which sensory, motor, and category variables were not perfectly coupled nor entirely independent, making it possible to observe evidence for abstract representations or purely grounded representations. To assess how the learned concept structure is represented in the brain, we examined brain regions implicated in flexible cognition (e.g., prefrontal and parietal cortex) that are most likely to encode an abstract representation removed from sensory-motor details. We also examined sensory-motor regions that might encode grounded sensory-motor based representations tuned for categorization. Using a cognitive model to estimate participants’ category rule and multivariate pattern analysis of fMRI data, we found left prefrontal cortex and MT coded for category in absence of information coding for stimulus or response. Because category was based on the stimulus, finding an abstract representation of category was not inevitable. Our results suggest that certain brain areas support categorization behaviour by constructing concept representations in a format akin to a symbol that differs from stimulus-motor codes.

Mental Mechanisms

Mind-Society ◽  
2019 ◽  
pp. 22-47
Author(s):  
Paul Thagard
Keyword(s):  
Cognitive Appraisal ◽  
Mental Representations ◽  
Special Kind ◽  
Neural Mechanisms ◽  
Emotional Information ◽  
Sensory Inputs ◽  
The World ◽  
Sensory Motor ◽  
Human Thinking ◽  
High Level

Psychological explanations based on representations and procedures can be deepened by showing how they emerge from neural mechanisms. Neurons represent aspects of the world by collective patterns of firing. These patterns can be bound into more complicated patterns that can transcend the limitations of sensory inputs. Semantic pointers are a special kind of representation that operates by binding neural patterns encompassing sensory, motor, verbal, and emotional information. The semantic pointer theory applies not only to the ordinary operations of mental representations like concepts and rules but also to the most high-level kinds of human thinking, including language, creativity, and consciousness. Semantic pointers also encompass emotions, construed as bindings that combine cognitive appraisal with physiological perception.

scholarly journals Linking Models with Brain Measures

2020 ◽  
Author(s):  
Bradley C. Love
Keyword(s):  
Information Flow ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Cognitive Model ◽  
Brain Regions ◽  
Learning Models ◽  
Model Based ◽  
Theoretical Significance ◽  
Brain Data ◽  
The Brain

Linking models and brain measures offers a number of advantages over standard analyses. Models that have been evaluated on previous datasets can provide theoretical constraints and assist in integrating findings across studies. Model-based analyses can be more sensitive and allow for evaluation of hypotheses that would not otherwise be addressable. For example, a cognitive model that is informed from several behavioural studies could be used to examine how multiple cognitive processes unfold across time in the brain. Models can be linked to brain measures in a number of ways. The information flow and constraints can be from model to brain, brain to model, or reciprocal. Likewise, the linkage from model and brain can be univariate or multivariate, as in studies that relate patterns of brain activity with model states. Models have multiple aspects that can be related to different facets of brain activity. This is well illustrated by deep learning models that have multiple layers or representations that can be aligned with different brain regions. Model-based approaches offer a lens on brain data that is complementary to popular multivariate decoding and representational similarity analysis approaches. Indeed, these approaches can realise greater theoretical significance when situated within a model-based approach.

High-Frequency EEG Activity

2017 ◽  
Author(s):  
Jean Gotman ◽  
Nathan E. Crone
Keyword(s):  
Clinical Significance ◽  
High Frequency ◽  
Brain Regions ◽  
Eeg Activity ◽  
Work Related ◽  
High Frequency Oscillations ◽  
Sensory Motor ◽  
The Brain ◽  
Important Marker

Activities with frequencies between 60 and 80 Hz and approximately 500 Hz are labeled here as high-frequency activities. They were largely ignored until the beginning of the millennium, but their importance is now well recognized. They can be divided into activities occurring in the healthy brain in relation to sensory, motor, and cognitive or memory activity and activities occurring in the epileptic brain in the form of brief events (high-frequency oscillations), which appear to be an important marker of the brain regions that are able to generate seizures of focal origin. In humans, most of the work related to these activities has been done in intracerebral electrodes, where they are relatively frequent and easy to identify. They have been recorded in scalp electroencephalograms in some circumstances, however. This chapter reviews the recording methods, the circumstances in which they occur, their mechanism of generation, and their clinical significance.

Songs to Syntax

2012 ◽  
pp. 70-80
Author(s):  
Robert C. Berwick
Keyword(s):  
Convergent Evolution ◽  
Vocal Learning ◽  
Brain Regions ◽  
Auditory Memory ◽  
Central Component ◽  
Common Descent ◽  
Sensory Modalities ◽  
Sensory Motor ◽  
The Rich ◽  
The Brain

Language comprises a central component of a complex that is sometimes called “the human capacity.” This complex seems to have crystallized fairly recently among a small group in East Africa of whom people are all descendants. Common descent has been important in the evolution of the brain, such that avian and mammalian brains may be largely homologous, particularly in the case of brain regions involved in auditory perception, vocalization and auditory memory. There has been convergent evolution of the capacity for auditory-vocal learning, and possibly for structuring of external vocalizations, such that apes lack the abilities that are shared between songbirds and humans. Language’s recent evolutionary origin suggests that the computational machinery underlying syntax arose via the introduction of a single, simple, combinatorial operation. Further, the relation of a simple combinatorial syntax to the sensory-motor and thought systems reveals language to be asymmetric in design: while it precisely matches the representations required for inner mental thought, acting as the “glue” that binds together other internal cognitive and sensory modalities, at the same time it poses computational difficulties for externalization, that is, parsing and speech or signed production. Despite this mismatch, language syntax leads directly to the rich cognitive array that marks us as a symbolic species.

Management of Glioblastoma Multiforme by Phytochemicals: Applications of Nanoparticle Based Targeted Drug Delivery System

2020 ◽  
Vol 21 ◽  
Author(s):  
Sayed Md Mumtaz ◽  
Gautam Bhardwaj ◽  
Shikha Goswami ◽  
Rajiv Kumar Tonk ◽  
Ramesh K. Goyal ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Glioblastoma Multiforme ◽  
Drug Delivery System ◽  
Delivery System ◽  
Genetic Disorder ◽  
Drug Regimen ◽  
Brain Regions ◽  
Radio Therapy ◽  
Novel Drug ◽  
The Brain

: The Glioblastoma Multiforme (GBM; grade IV astrocytoma) exhort tumor of star-shaped glial cell in the brain. It is a fast-growing tumor that spreads to nearby brain regions specifically to cerebral hemispheres in frontal and temporal lobes. The etiology of GBM is unknown, but major risk factors are genetic disorder like neurofibromatosis and schwanomatosis which develop the tumor in the nervous system. The management of GBM with chemo-radio therapy leads to resistance and current drug regimen like Temozolomide (TMZ) is less efficacious. The reasons behind failure of drugs are due to DNA alkylation in cell cycle by enzyme DNA guanidase and mitochondrial dysfunction. Naturally occurring bio-active compounds from plants known as phytochemicals, serve as vital sources for anti-cancer drugs. Some typical examples include taxol analogs, vinca alkaloids such as vincristine, vinblastine, podophyllotoxin analogs, camptothecin, curcumin, aloe emodin, quercetin, berberine e.t.c. These phytochemicals often act via regulating molecular pathways which are implicated in growth and progression of cancers. However the challenges posed by the presence of BBB/BBTB to restrict passage of these phytochemicals, culminates in their low bioavailability and relative toxicity. In this review we integrated nanotech as novel drug delivery system to deliver phytochemicals from traditional medicine to the specific site within the brain for the management of GBM.

Neuro-Clinical Signatures of Language Impairments: A Theoretical Framework for Function-to-structure Mapping in Clinics

2020 ◽  
Vol 20 (9) ◽  
pp. 800-811 ◽  
Author(s):  
Ferath Kherif ◽  
Sandrine Muller
Keyword(s):  
Brain Mapping ◽  
Theoretical Framework ◽  
Brain Regions ◽  
Language Impairments ◽  
Structure Mapping ◽  
Language Functions ◽  
The Past ◽  
Language Recovery ◽  
The Brain ◽  
Bow Tie

In the past decades, neuroscientists and clinicians have collected a considerable amount of data and drastically increased our knowledge about the mapping of language in the brain. The emerging picture from the accumulated knowledge is that there are complex and combinatorial relationships between language functions and anatomical brain regions. Understanding the underlying principles of this complex mapping is of paramount importance for the identification of the brain signature of language and Neuro-Clinical signatures that explain language impairments and predict language recovery after stroke. We review recent attempts to addresses this question of language-brain mapping. We introduce the different concepts of mapping (from diffeomorphic one-to-one mapping to many-to-many mapping). We build those different forms of mapping to derive a theoretical framework where the current principles of brain architectures including redundancy, degeneracy, pluri-potentiality and bow-tie network are described.

scholarly journals Neuroinflammation and protein pathology in Parkinson’s disease dementia

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Antonina Kouli ◽  
Marta Camacho ◽  
Kieren Allinson ◽  
Caroline H. Williams-Gray
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
T Lymphocytes ◽  
Substantia Nigra ◽  
Amyloid Β ◽  
Brain Regions ◽  
Parkinson’S Disease Dementia ◽  
Activated Microglia ◽  
Cell Counts ◽  
The Brain

AbstractParkinson’s disease dementia is neuropathologically characterized by aggregates of α-synuclein (Lewy bodies) in limbic and neocortical areas of the brain with additional involvement of Alzheimer’s disease-type pathology. Whilst immune activation is well-described in Parkinson’s disease (PD), how it links to protein aggregation and its role in PD dementia has not been explored. We hypothesized that neuroinflammatory processes are a critical contributor to the pathology of PDD. To address this hypothesis, we examined 7 brain regions at postmortem from 17 PD patients with no dementia (PDND), 11 patients with PD dementia (PDD), and 14 age and sex-matched neurologically healthy controls. Digital quantification after immunohistochemical staining showed a significant increase in the severity of α-synuclein pathology in the hippocampus, entorhinal and occipitotemporal cortex of PDD compared to PDND cases. In contrast, there was no difference in either tau or amyloid-β pathology between the groups in any of the examined regions. Importantly, we found an increase in activated microglia in the amygdala of demented PD brains compared to controls which correlated significantly with the extent of α-synuclein pathology in this region. Significant infiltration of CD4+ T lymphocytes into the brain parenchyma was commonly observed in PDND and PDD cases compared to controls, in both the substantia nigra and the amygdala. Amongst PDND/PDD cases, CD4+ T cell counts in the amygdala correlated with activated microglia, α-synuclein and tau pathology. Upregulation of the pro-inflammatory cytokine interleukin 1β was also evident in the substantia nigra as well as the frontal cortex in PDND/PDD versus controls with a concomitant upregulation in Toll-like receptor 4 (TLR4) in these regions, as well as the amygdala. The evidence presented in this study show an increased immune response in limbic and cortical brain regions, including increased microglial activation, infiltration of T lymphocytes, upregulation of pro-inflammatory cytokines and TLR gene expression, which has not been previously reported in the postmortem PDD brain.

scholarly journals An architectonic type principle in the development of laminar patterns of cortico-cortical connections

2021 ◽  
Author(s):  
Sarah F. Beul ◽  
Alexandros Goulas ◽  
Claus C. Hilgetag
Keyword(s):  
Structural Connectivity ◽  
Macaque Monkey ◽  
Brain Regions ◽  
Adult Brain ◽  
Mammalian Brain ◽  
Cortical Connections ◽  
Cortical Projections ◽  
Structural Connections ◽  
High Degree ◽  
The Brain

AbstractStructural connections between cortical areas form an intricate network with a high degree of specificity. Many aspects of this complex network organization in the adult mammalian cortex are captured by an architectonic type principle, which relates structural connections to the architectonic differentiation of brain regions. In particular, the laminar patterns of projection origins are a prominent feature of structural connections that varies in a graded manner with the relative architectonic differentiation of connected areas in the adult brain. Here we show that the architectonic type principle is already apparent for the laminar origins of cortico-cortical projections in the immature cortex of the macaque monkey. We find that prenatal and neonatal laminar patterns correlate with cortical architectonic differentiation, and that the relation of laminar patterns to architectonic differences between connected areas is not substantially altered by the complete loss of visual input. Moreover, we find that the degree of change in laminar patterns that projections undergo during development varies in proportion to the relative architectonic differentiation of the connected areas. Hence, it appears that initial biases in laminar projection patterns become progressively strengthened by later developmental processes. These findings suggest that early neurogenetic processes during the formation of the brain are sufficient to establish the characteristic laminar projection patterns. This conclusion is in line with previously suggested mechanistic explanations underlying the emergence of the architectonic type principle and provides further constraints for exploring the fundamental factors that shape structural connectivity in the mammalian brain.

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