scholarly journals A Roadmap for Understanding Memory: Decomposing Cognitive Processes into Operations and Representations

2019 ◽  
Author(s):  
Rosemary Cowell ◽  
Morgan Barense ◽  
Patrick Sadil
Keyword(s):  
Division Of Labor ◽  
Cognitive Functions ◽  
Declarative Memory ◽  
Behavioral Control ◽  
Representational Content ◽  
Neural Mechanism ◽  
Brain Regions ◽  
Medial Temporal Lobes ◽  
Pattern Completion ◽  
High Level

Thanks to patients Phineas Gage and Henry Molaison, we have long known that behavioral control depends on the frontal lobes, whereas declarative memory depends on the medial temporal lobes. For decades, cognitive functions – behavioral control, declarative memory – have served as labels for characterizing the division of labor in cortex. This approach has made enormous contributions to understanding how the brain enables the mind, providing a systems-level explanation of brain function that constrains lower-level investigations of neural mechanism. Today, the approach has evolved such that functional labels are often applied to brain networks rather than focal brain regions. Furthermore, the labels have diversified to include both broadly-defined cognitive functions (declarative memory, visual perception) and more circumscribed mental processes (recollection, familiarity, priming). We ask whether a process – a high-level mental phenomenon corresponding to an introspectively-identifiable cognitive event – is the most productive label for dissecting memory. For example, the process of recollection conflates a neurocomputational operation (pattern completion-based retrieval) with a class of representational content (associative, high-dimensional, episodic-like memories). Because a full theory of memory must identify operations and representations separately, and specify how they interact, we argue that processes like recollection constitute inadequate labels for characterizing neural mechanisms. Instead, we advocate considering the component operations and representations of mnemonic processes in isolation, when examining their neural underpinnings. For the neuroanatomical organization of memory, the evidence suggests that pattern completion is recapitulated widely across cortex, but the division of labor between cortical sites can be explained by representational content.

On the Principles of Imagination and Creativity

2019 ◽  
pp. 1-62
Author(s):  
Rajashree Chaurasia
Keyword(s):  
Cognitive Functions ◽  
Industrial Revolution ◽  
Brain Regions ◽  
The Other ◽  
Evolutionary Perspective ◽  
Human Beings ◽  
Historical Perspectives ◽  
Fourth Industrial Revolution ◽  
High Level ◽  
Creativity And Innovation

Human beings are the only mammals to be able to utilize high-level cognitive functions to build knowledge, innovate, and communicate their complex ideas. Imagination, creativity, and innovation are interlinked in the sense that one leads to the other. This chapter details the concepts of imagery, imagination, and creativity and their inter-relationships in the first section. Next, the author discusses the historical perspectives of imagination pertaining to the accounts of famous philosophers and psychologists like Aristotle, Kant, Hume, Descartes, Sartre, Husserl, and Wittgenstein. Section 3 and 4 present the neuro-biological correlates of imagination and creativity, respectively. Brain regions, neuronal circuits, genetic basis, as well as the evolutionary perspective of imagination and creativity are elicited in these sections. Finally, creativity and innovation are explored as to how they will contribute to knowledge build-up and advances in science, engineering, and business in the fourth industrial revolution and the imagination age.

scholarly journals The locus of recognition memory signals in human cortex depends on the complexity of the memory representations

2021 ◽  
Author(s):  
D. Merika W. Sanders ◽  
Rosemary A. Cowell
Keyword(s):  
Recognition Memory ◽  
Medial Temporal Lobe ◽  
Declarative Memory ◽  
Memory Task ◽  
Representational Content ◽  
Brain Regions ◽  
Complex Stimuli ◽  
Memory Representations ◽  
Memory Signals ◽  
Feature Memory

Representational theories predict that brain regions contribute to cognition according to the information they represent (e.g., simple versus complex), contradicting the traditional notion that brain regions are specialized for cognitive functions (e.g., perception versus memory). In support of representational accounts, substantial evidence now attests that the Medial Temporal Lobe (MTL) is not specialized solely for long-term declarative memory, but underpins other functions including perception and future-imagining for complex stimuli and events. However, a complementary prediction has been less well explored, namely that the cortical locus of declarative memory may fall outside the MTL if the to-be-remembered content is sufficiently simple. Specifically, the locus should coincide with the optimal neural code for the representations being retrieved. To test this prediction, we manipulated the complexity of the to-be-remembered representations in a recognition memory task. First, participants in the scanner viewed novel 3D objects and scenes, and we used multivariate analyses to identify regions in the ventral visual-MTL pathway that preferentially coded for either simple features of the stimuli, or complex conjunctions of those features. Next, in a separate scan, we tested recognition memory for these stimuli and performed neuroimaging contrasts that revealed two memory signals ‒ feature memory and conjunction memory. Feature memory signals were found in visual cortex, while conjunction memory signals emerged in MTL. Further, the regions optimally representing features via preferential feature-coding coincided with those exhibiting feature memory signals. These findings suggest that representational content, rather than cognitive function, is the primary organizing principle in the ventral visual-MTL pathway.

scholarly journals A functional dissociation between language and multiple-demand systems revealed in patterns of BOLD signal fluctuations

2014 ◽  
Vol 112 (5) ◽  
pp. 1105-1118 ◽  
Author(s):  
Idan Blank ◽  
Nancy Kanwisher ◽  
Evelina Fedorenko
Keyword(s):  
Cognitive Processing ◽  
Language Processing ◽  
Cognitive Functions ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Story Comprehension ◽  
Blood Oxygen Level ◽  
Two Systems ◽  
Dependent Signal ◽  
High Level

What is the relationship between language and other high-level cognitive functions? Neuroimaging studies have begun to illuminate this question, revealing that some brain regions are quite selectively engaged during language processing, whereas other “multiple-demand” (MD) regions are broadly engaged by diverse cognitive tasks. Nonetheless, the functional dissociation between the language and MD systems remains controversial. Here, we tackle this question with a synergistic combination of functional MRI methods: we first define candidate language-specific and MD regions in each subject individually (using functional localizers) and then measure blood oxygen level-dependent signal fluctuations in these regions during two naturalistic conditions (“rest” and story-comprehension). In both conditions, signal fluctuations strongly correlate among language regions as well as among MD regions, but correlations across systems are weak or negative. Moreover, data-driven clustering analyses based on these inter-region correlations consistently recover two clusters corresponding to the language and MD systems. Thus although each system forms an internally integrated whole, the two systems dissociate sharply from each other. This independent recruitment of the language and MD systems during cognitive processing is consistent with the hypothesis that these two systems support distinct cognitive functions.

Compressed sensorimotor-to-transmodal hierarchical organization in schizophrenia

2021 ◽  
pp. 1-14
Author(s):  
Debo Dong ◽  
Dezhong Yao ◽  
Yulin Wang ◽  
Seok-Jun Hong ◽  
Sarah Genon ◽  
...  
Keyword(s):  
Sensory Information ◽  
Resting State Fmri ◽  
Brain Regions ◽  
High Order ◽  
Hierarchical Organization ◽  
System Level ◽  
Integrative System ◽  
Sensorimotor Region ◽  
Cortical Hierarchy ◽  
High Level

Abstract Background Schizophrenia has been primarily conceptualized as a disorder of high-order cognitive functions with deficits in executive brain regions. Yet due to the increasing reports of early sensory processing deficit, recent models focus more on the developmental effects of impaired sensory process on high-order functions. The present study examined whether this pathological interaction relates to an overarching system-level imbalance, specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Methods We applied a novel combination of connectome gradient and stepwise connectivity analysis to resting-state fMRI to characterize the sensorimotor-to-transmodal cortical hierarchy organization (96 patients v. 122 controls). Results We demonstrated compression of the cortical hierarchy organization in schizophrenia, with a prominent compression from the sensorimotor region and a less prominent compression from the frontal−parietal region, resulting in a diminished separation between sensory and fronto-parietal cognitive systems. Further analyses suggested reduced differentiation related to atypical functional connectome transition from unimodal to transmodal brain areas. Specifically, we found hypo-connectivity within unimodal regions and hyper-connectivity between unimodal regions and fronto-parietal and ventral attention regions along the classical sensation-to-cognition continuum (voxel-level corrected, p < 0.05). Conclusions The compression of cortical hierarchy organization represents a novel and integrative system-level substrate underlying the pathological interaction of early sensory and cognitive function in schizophrenia. This abnormal cortical hierarchy organization suggests cascading impairments from the disruption of the somatosensory−motor system and inefficient integration of bottom-up sensory information with attentional demands and executive control processes partially account for high-level cognitive deficits characteristic of schizophrenia.

scholarly journals Depletion of acetate-producing bacteria from the gut microbiota facilitates cognitive impairment through the gut-brain neural mechanism in diabetic mice

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Hong Zheng ◽  
Pengtao Xu ◽  
Qiaoying Jiang ◽  
Qingqing Xu ◽  
Yafei Zheng ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Gut Microbiota ◽  
Cognitive Functions ◽  
Neural Mechanism ◽  
Fecal Microbiota ◽  
Protective Role ◽  
Fecal Microbiota Transplant ◽  
Memory Impairments ◽  
The Impact

Abstract Background Modification of the gut microbiota has been reported to reduce the incidence of type 1 diabetes mellitus (T1D). We hypothesized that the gut microbiota shifts might also have an effect on cognitive functions in T1D. Herein we used a non-absorbable antibiotic vancomycin to modify the gut microbiota in streptozotocin (STZ)-induced T1D mice and studied the impact of microbial changes on cognitive performances in T1D mice and its potential gut-brain neural mechanism. Results We found that vancomycin exposure disrupted the gut microbiome, altered host metabolic phenotypes, and facilitated cognitive impairment in T1D mice. Long-term acetate deficiency due to depletion of acetate-producing bacteria resulted in the reduction of synaptophysin (SYP) in the hippocampus as well as learning and memory impairments. Exogenous acetate supplement or fecal microbiota transplant recovered hippocampal SYP level in vancomycin-treated T1D mice, and this effect was attenuated by vagal inhibition or vagotomy. Conclusions Our results demonstrate the protective role of microbiota metabolite acetate in cognitive functions and suggest long-term acetate deficiency as a risk factor of cognitive decline.

scholarly journals Comparison of Activation in the Prefrontal Cortex of Native Speakers of Mandarin by Ability of Japanese as a Second Language Using a Novel Speaking Task

Healthcare ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 412
Author(s):  
Li Cong ◽  
Hideki Miyaguchi ◽  
Chinami Ishizuki
Keyword(s):  
Second Language ◽  
Prefrontal Cortex ◽  
Cognitive Load ◽  
Near Infrared ◽  
Native Speakers ◽  
Brain Activation ◽  
Brain Regions ◽  
Strong Inhibition ◽  
Functional Near Infrared Spectroscopy ◽  
High Level

Evidence shows that second language (L2) learning affects cognitive function. Here in this work, we compared brain activation in native speakers of Mandarin (L1) who speak Japanese (L2) between and within two groups (high and low L2 ability) to determine the effect of L2 ability in L1 and L2 speaking tasks, and to map brain regions involved in both tasks. The brain activation during task performance was determined using prefrontal cortex blood flow as a proxy, measured by functional near-infrared spectroscopy (fNIRS). People with low L2 ability showed much more brain activation when speaking L2 than when speaking L1. People with high L2 ability showed high-level brain activation when speaking either L2 or L1. Almost the same high-level brain activation was observed in both ability groups when speaking L2. The high level of activation in people with high L2 ability when speaking either L2 or L1 suggested strong inhibition of the non-spoken language. A wider area of brain activation in people with low compared with high L2 ability when speaking L2 is considered to be attributed to the cognitive load involved in code-switching L1 to L2 with strong inhibition of L1 and the cognitive load involved in using L2.

scholarly journals Spine impairment in mice high-expressing neuregulin 1 due to LIMK1 activation

2021 ◽  
Vol 12 (4) ◽  
Author(s):  
Peng Chen ◽  
Hongyang Jing ◽  
Mingtao Xiong ◽  
Qian Zhang ◽  
Dong Lin ◽  
...  
Keyword(s):  
Neural Development ◽  
Protein Level ◽  
Brain Regions ◽  
Postmortem Brain ◽  
Pathophysiological Mechanism ◽  
Brain Disorders ◽  
Spine Density ◽  
Genes Encoding ◽  
High Level ◽  
And Function

AbstractThe genes encoding for neuregulin1 (NRG1), a growth factor, and its receptor ErbB4 are both risk factors of major depression disorder and schizophrenia (SZ). They have been implicated in neural development and synaptic plasticity. However, exactly how NRG1 variations lead to SZ remains unclear. Indeed, NRG1 levels are increased in postmortem brain tissues of patients with brain disorders. Here, we studied the effects of high-level NRG1 on dendritic spine development and function. We showed that spine density in the prefrontal cortex and hippocampus was reduced in mice (ctoNrg1) that overexpressed NRG1 in neurons. The frequency of miniature excitatory postsynaptic currents (mEPSCs) was reduced in both brain regions of ctoNrg1 mice. High expression of NRG1 activated LIMK1 and increased cofilin phosphorylation in postsynaptic densities. Spine reduction was attenuated by inhibiting LIMK1 or blocking the NRG1–LIMK1 interaction, or by restoring NRG1 protein level. These results indicate that a normal NRG1 protein level is necessary for spine homeostasis and suggest a pathophysiological mechanism of abnormal spines in relevant brain disorders.

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

2016 ◽  
Vol 28 (11) ◽  
pp. 1749-1759 ◽  
Author(s):  
Benjamin D. Zinszer ◽  
Andrew J. Anderson ◽  
Olivia Kang ◽  
Thalia Wheatley ◽  
Rajeev D. S. Raizada
Keyword(s):  
Analogical Reasoning ◽  
Language Translation ◽  
Structural Alignment ◽  
Word Meaning ◽  
Representational Content ◽  
English Word ◽  
English Speakers ◽  
Native Languages ◽  
Neural Representations ◽  
High Level

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. Groups of Chinese and English speakers underwent fMRI scanning while reading words in their respective native languages. Simply by aligning structures representing the two groups' neural semantic spaces, we successfully infer all seven Chinese–English word translations. Beyond language translation, conceptual structural alignment underlies many aspects of high-level cognition, and this work opens the door to deriving many such alignments directly from neural representational content.

scholarly journals Hierarchical decision processes that operate over distinct timescales underlie choice and changes in strategy

2016 ◽  
Vol 113 (31) ◽  
pp. E4531-E4540 ◽  
Author(s):  
Braden A. Purcell ◽  
Roozbeh Kiani
Keyword(s):  
Decision Making ◽  
Neural Mechanism ◽  
Decision Processes ◽  
Response Strategy ◽  
Limited Information ◽  
Decision Strategy ◽  
Stimulus Response ◽  
Hierarchical Decision ◽  
The Right ◽  
High Level

Decision-making in a natural environment depends on a hierarchy of interacting decision processes. A high-level strategy guides ongoing choices, and the outcomes of those choices determine whether or not the strategy should change. When the right decision strategy is uncertain, as in most natural settings, feedback becomes ambiguous because negative outcomes may be due to limited information or bad strategy. Disambiguating the cause of feedback requires active inference and is key to updating the strategy. We hypothesize that the expected accuracy of a choice plays a crucial rule in this inference, and setting the strategy depends on integration of outcome and expectations across choices. We test this hypothesis with a task in which subjects report the net direction of random dot kinematograms with varying difficulty while the correct stimulus−response association undergoes invisible and unpredictable switches every few trials. We show that subjects treat negative feedback as evidence for a switch but weigh it with their expected accuracy. Subjects accumulate switch evidence (in units of log-likelihood ratio) across trials and update their response strategy when accumulated evidence reaches a bound. A computational framework based on these principles quantitatively explains all aspects of the behavior, providing a plausible neural mechanism for the implementation of hierarchical multiscale decision processes. We suggest that a similar neural computation—bounded accumulation of evidence—underlies both the choice and switches in the strategy that govern the choice, and that expected accuracy of a choice represents a key link between the levels of the decision-making hierarchy.

Association of Hemoglobin A1C With TDP-43 Pathology in Community-Based Elders

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012025
Author(s):  
Shahram Oveisgharan ◽  
Ana W. Capuano ◽  
Sukriti Nag ◽  
Sonal Agrawal ◽  
Lisa L. Barnes ◽  
...  
Keyword(s):  
Severity Score ◽  
Hemoglobin A1c ◽  
Oldest Old ◽  
Brain Regions ◽  
Inverse Association ◽  
Community Based ◽  
Cytoplasmic Inclusions ◽  
The Mean ◽  
High Level ◽  
Relationship Of

Objective.We tested the hypothesis that an inverse association exists between diabetes mellitus (DM) and hemoglobin A1C (A1C) with Transactive response DNA binding protein 43 (TDP-43) levels in older adults.Methods.We leveraged antemortem and postmortem data of decedents from three community-based clinical-pathological studies. DM status, A1C levels, and medications for DM were documented annually. TDP-43 cytoplasmic inclusions, evaluated in 6 brain regions using immunohistochemistry, were used to obtain a semiquantitative TDP-43 score (0-5) in each region, and scores were averaged across regions to obtain a TDP-43 severity score. We used linear regressions to test the association of DM and A1C with the TDP-43 severity score.Results.On average, participants (n=817) were 90 years old at the time of death, three fourth were women, and one fourth had DM. The mean A1C was 6.0% (SD=0.6). TDP-43 was observed in 54% of participants, and the mean TDP-43 score was 0.7 (range 0-4.5). A higher level of A1C was associated with a lower TDP-43 score (estimate=-0.156, S.E.=0.060, p=0.009) while DM had a borderline inverse association with the TDP-43 score (estimate=-0.163, S.E.=0.087, p=0.060). The association of higher levels of A1C with lower TDP-43 scores persisted after further adjustment by Apolipoprotein ε4, vascular risk factors, stroke, and hypoglycemic medications. Exclusion of the oldest old participants did not change the results.Conclusion.Overall, the results suggest that a high level of A1C is associated with less TDP-43 proteinopathy in older persons while the relationship of DM with TDP-43 needs further study.

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