A Computational Cognitive Model of the Brain

2008 ◽  
Vol 2 (4) ◽  
pp. 85-99 ◽  
Author(s):  
Zhiwei Shi ◽  
Hong Hu ◽  
Zhongzhi Shi
Keyword(s):  
Cognitive Model ◽  
The Brain

Diagnosis as a Detriment: A Cognitive Approach to Understanding the Depressive Experience

2015 ◽  
Vol 17 (2) ◽  
pp. 125-134 ◽  
Author(s):  
Evan Hy Einstein
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Theoretical Model ◽  
Mental Health Care ◽  
Cognitive Model ◽  
Clinical Applications ◽  
Psychotropic Medications ◽  
Cognitive Mechanisms ◽  
Cognitive Approach ◽  
The Brain

Depression is currently understood within a biomedical paradigm. This paradigm is an example of reductionism; people are clinically diagnosed and categorized based on behavior and affect, while they are then prescribed psychotropic medications based on an inconclusively correlated neurotransmitter imbalance in the brain. In this article, clinical diagnosis and labeling are explored with respect to their detrimental potential. A framework of embodied cognition is used to conceptualize a cognitive model of depressive experience. This theoretical model explores the potentially self-reinforcing cognitive mechanisms behind a depressive experience, with the goal of highlighting the possibility of diagnosis as a detrimental influence on these mechanisms. The aim of this article is to further a discussion about our current mental health care paradigm and provide an explanation as to how it could cause harm to some. Clinical applications of the model are also discussed pertaining to the potential of rendering formal dichotomist diagnoses irrelevant to the ultimate goal of helping people feel better.

Psycho-Cognitive Model of Knowledge Creation Theory

2021 ◽  
Author(s):  
Sunday Bolade
Keyword(s):  
Knowledge Creation ◽  
Personal Experience ◽  
Cognitive Process ◽  
Cognitive Model ◽  
Sensory Organs ◽  
Mental Processes ◽  
Cognitive Perspective ◽  
Skill Sets ◽  
New Concepts ◽  
The Brain

Humans perform activities collaboratively or individually, and these activities, more often than not, involve both physical and mental processes. However, irrespective of whether individual or collective functioning, knowledge creation is a personal experience. Nevertheless, the general tenet of this paper is that knowledge is created in a human’s mind and resides in the head. Hence, it posits that knowledge creation is cognitive (associated with the neurological structures of the brain) and psychological (involving consciousness)—a psycho-cognitive process. This study thus employs a “Cognaction” mechanism that is based on the assumptions captured below. The mechanism premised that the human cognitive chamber consists of 3C modes of comprehension (for interpreting stimuli transmitted to the brain by sensory organs), contextualisation (for mindful connecting of chunks to existing schemas), and conceptualisation (for evaluative reflection in a manner that leads to drawing inference and building themes or new concepts). It demonstrates that as diverse skill sets are applied to a task, they generate varieties of effects and outcomes. The outcomes though are distinctive and at the same time are cospecialised. Thus, the psycho-cognitive perspective demonstrates knowledge creation as a cocreation process and sees knowledge as a mix of cocreated, cognitive structures. In view of these, the study provides the missing explanation on how the knowledge archetypes emerged. And it provides the missing link between the belief that “knowledge is created in the head” and knowledge creation theory.

Semantic and Formal Representation of Cognitive Models for the Metacognitive Architecture CARINA

2021 ◽  
pp. 54-72
Author(s):  
Alba J. Jerónimo ◽  
María P. Barrera ◽  
Manuel F. Caro ◽  
Adán A. Gómez
Keyword(s):  
Knowledge Representation ◽  
Semantic Memory ◽  
Cognitive Model ◽  
Semantic Knowledge ◽  
Cognitive Models ◽  
Formal Representation ◽  
Object Properties ◽  
Internal Information ◽  
Processing Mechanisms ◽  
The Brain

A cognitive model is a computational model of internal information processing mechanisms of the brain for the purposes of comprehension and prediction. CARINA metacognitive architecture runs cognitive models. However, CARINA does not currently have mechanisms to store and learn from cognitive models executed in the past. Semantic knowledge representation is a field of study which concentrates on using formal symbols to a collection of propositions, objects, object properties, and relations among objects. In CARINA Beliefs are a form of represent the semantic knowledge. The aim of this chapter is to formally describe a CARINA-based cognitive model through of denotational mathematics and to represent these models using a technique of semantic knowledge representation called beliefs. All the knowledge received by CARINA is stored in the semantic memory in the form of beliefs. Thus, a cognitive model represented through beliefs will be ready to be stored in semantic memory of the metacognitive architecture CARINA. Finally, an illustrative example is presented.

scholarly journals ‘Chitta’, “The Mind-stuff” as a Cognitive Apparatus: Model of mind and process of cognition as in Yogasutra of Patanjali

2014 ◽  
Vol 2 (1) ◽  
pp. 10-16
Author(s):  
K Upadhyay-Dhungel ◽  
BK Dahal
Keyword(s):  
Qualitative Method ◽  
Cognitive Model ◽  
External World ◽  
Psychological Therapy ◽  
Modern Concept ◽  
Medical Sciences ◽  
Psychological Counseling ◽  
Medical College ◽  
The Mind ◽  
The Brain

Background and Objectives: Medical sciences have developed tremendously but yet it has to understand the brain, mind, consciousness and cognition process. In this article, authors have made an attempt to present a process of cognition with a model of mind explained in yoga sutra of Patanjali. Material and Methods: Understanding the mind with the modern scientific tools is often difficult. Here an attempt has been made to understand mind with the help of various literature in yoga especially in yoga sutra of patanjali, a valid text of yoga. Hermeneutical approach, a method used in qualitative method of inquiry is used for this study. Reading, re-reading the texts and finding the meaning out of the text is the process used. Results: A model of mind has been proposed as finding of the study. This model of mind has a ‘chitta’ (Mind stuff) as a cognitive apparatus and important component for cognition. ‘Chitta’ interacts with the external manifested world (Prakriti). ‘Chitta’ has Mana, Buddhi and Ego as Antakahrana (internal organ) and ‘Indriyas’ (Five Gyanendriyas and Five Karmaindriyas) as external organ. This concept of mind and cognition works for the plane of ‘chitta-vritti’ state where vrittis are the external world. But YSP also talks about next plane of cognition which is beyond the scope of this study. Conclusion: A cognitive model explaining the concept of mind forms a major finding of this research. This finding may initiate future researches in the field of understanding the mental processing and acts as links between ancient wisdom of yoga and modern concept on mind and cognition and how they can complement each other. This model of concept of mind can also be used as concept for psychological counseling and psychological therapy. DOI: http://dx.doi.org/10.3126/jmcjms.v2i1.11390   Janaki Medical College Journal of Medical Sciences (2014) Vol. 2 (1): 10-16

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.

A Computational Cognitive Model of the Brain

2011 ◽  
pp. 1-17
Author(s):  
Zhiwei Shi ◽  
Hong Hu ◽  
Zhongzhi Shi
Keyword(s):  
Knowledge Representation ◽  
Human Brain ◽  
Experimental Evidence ◽  
Graphical Model ◽  
Cognitive Model ◽  
Similarity Measurement ◽  
Top Down ◽  
Knowledge Accumulation ◽  
Computational Explanation ◽  
The Brain

Recent fruitful progresses on brain science have largely broadened our understanding of the cerebrum. These great works led us to propose a computational cognitive model based on a graphical model that we carried out before. The model possesses many attractive properties, including distinctive knowledge representation, the capability of knowledge accumulation, active (top-down) attention, subjective similarity measurement, and attention-guided disambiguation. It also has “consciousness” and can even “think” and “make inference.” To some extent, it works just like the human brain does. The experimental evidence demonstrates that it can give reasonable computational explanation on the human phenomenon of forgetting. Although there are still some undetermined details and neurobiological mechanisms deserving consideration, our work presents a meaningful attempt to give further insights into the brain’s functions.

What drives our brain? – PFO as a physical being outside our universe –

2016 ◽  
pp. 4070-4087
Author(s):  
Takashi Taneichi
Keyword(s):  
Dimensional Space ◽  
Cognitive Model ◽  
The Unconscious ◽  
The Neural Network ◽  
Internal Bleeding ◽  
Local Functions ◽  
Modern Physics ◽  
The Frame Problem ◽  
The Brain ◽  
External Injury

Local functions of the brain can be complemented by other parts by training, even if they were lost by an accident such as external injury and internal bleeding. This is the dynamical redistribution of functions inside the brain. It can be regarded as a result of the Operating System (OS) function of the brain, on the analogy of computers. On the other hand, the passive consciousness hypothesis is known to be a powerful cognitive model in the sense that it figures out the difficult problems concerning consciousness such as the frame problem, binding problem, etc. Intrinsic problem of the model, however, lies in the dubious mechanism by which collective opinions are decided by “majority vote” in the unconscious system and are collected to the local conscious system in a bottom-up manner. No one has elucidated, so far, how the unconscious system and the conscious one are connected in the neural network. The Parasite Fermion Model is a physical model that solves those problems. The Model asserts that, only by assuming the multi-dimensional universe that is nowadays commonly discussed in the modern physics and two types of fermions (material particles), there exists the materialistic subject, called Parasite Fermion Object (PFO), in the extra-dimensional space. One can avoid above-mentioned difficulties, by assuming that the PFO plays a significant role in the OS function and decision process of the unconscious system.

scholarly journals 4488 Neural Network of the Cognitive Model of Reading

2020 ◽  
Vol 4 (s1) ◽  
pp. 140-141
Author(s):  
Joseph Posner ◽  
Vivian Dickens ◽  
Andrew DeMarco ◽  
Sarah Snider ◽  
Peter Turkeltaub ◽  
...  
Keyword(s):  
Neural Networks ◽  
Functional Connectivity ◽  
Cognitive Processing ◽  
Word Reading ◽  
Cognitive Model ◽  
Network Connectivity ◽  
Cognitive Models ◽  
Neuronal Interactions ◽  
Language Areas ◽  
The Brain

OBJECTIVES/GOALS: A particularly debilitating consequence of stroke is alexia, an acquired impairment in reading. Cognitive models aim to characterize how information is processed based on behavioral data. If we can concurrently characterize how neural networks process that information, we can enhance the models to reflect the neuronal interactions that drive them. METHODS/STUDY POPULATION: There will be 10 unimpaired adult readers. Two functional localizer tasks, deigned to consistently activate robust language areas, identify the regions of interest that process the cognitive reading functions (orthography, phonology, semantics). Another task, designed for this experiment, analyses the reading-related functional-connectivity between these areas by presenting words classified along the attributes of frequency, concreteness, and regularity, which utilize specific cognitive routes, and a visual control. Connectivity is analyzed during word reading overall vs. a control condition to determine overall reading-related connectivity, and while reading words that have high vs. low attribute values, to determine if cognitive processing routes bias the neural reading network connectivity. RESULTS/ANTICIPATED RESULTS: The localizer analysis is expected to result in the activation of canonical reading areas. The degree of functional connectivity observed between these regions is expected to depend on the degree to which each cognitive route is utilized to read a given word. After orthographic, phonologic, and semantic areas have been identified, the connectivity analysis should show that there is high correlation between all three types of areas during reading compared to the control condition. Then the frequency, regularity, and concreteness of the words being read should alter the reliance on the pathways between these area types. This would support the hypothesized pattern of connectivity as predicted by the cognitive reading routes. Otherwise, it will show how the neural reading network differs from the cognitive model. DISCUSSION/SIGNIFICANCE OF IMPACT: The results will determine the relationship between the cognitive reading model and the neural reading network. Cognitive models show what processes occur in the brain, but neural networks show how these processes occur. By relating these components, we obtain a more complete view of reading in the brain, which can inform future alexia treatments.

scholarly journals Visual motion assists in social cognition

2020 ◽  
Vol 117 (50) ◽  
pp. 32165-32168
Author(s):  
Arvid Guterstam ◽  
Michael S. A. Graziano
Keyword(s):  
Social Cognition ◽  
Visual Motion ◽  
Cognitive Model ◽  
Object Motion ◽  
Motion Processing ◽  
Attentional State ◽  
Motion Direction ◽  
Motion Signal ◽  
Visual Motion Processing ◽  
The Brain

Recent evidence suggests a link between visual motion processing and social cognition. When person A watches person B, the brain of A apparently generates a fictitious, subthreshold motion signal streaming from B to the object of B’s attention. These previous studies, being correlative, were unable to establish any functional role for the false motion signals. Here, we directly tested whether subthreshold motion processing plays a role in judging the attention of others. We asked, if we contaminate people’s visual input with a subthreshold motion signal streaming from an agent to an object, can we manipulate people’s judgments about that agent’s attention? Participants viewed a display including faces, objects, and a subthreshold motion hidden in the background. Participants’ judgments of the attentional state of the faces was significantly altered by the hidden motion signal. Faces from which subthreshold motion was streaming toward an object were judged as paying more attention to the object. Control experiments showed the effect was specific to the agent-to-object motion direction and to judging attention, not action or spatial orientation. These results suggest that when the brain models other minds, it uses a subthreshold motion signal, streaming from an individual to an object, to help represent attentional state. This type of social-cognitive model, tapping perceptual mechanisms that evolved to process physical events in the real world, may help to explain the extraordinary cultural persistence of beliefs in mind processes having physical manifestation. These findings, therefore, may have larger implications for human psychology and cultural belief.

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