scholarly journals Change Is Good for the Brain: Activity Diversity and Cognitive Functioning Across Adulthood

2020 ◽  
Author(s):  
Soomi Lee ◽  
Susan T Charles ◽  
David M Almeida
Keyword(s):  
Executive Functioning ◽  
Cognitive Functioning ◽  
Brain Activity ◽  
Paid Work ◽  
Work Time ◽  
Activity Data ◽  
Future Work ◽  
Increased Activity ◽  
The Brain ◽  
Cognitive Data

Abstract Objectives Participating in a variety of daily activities (i.e., activity diversity) requires people to adjust to a variety of situations and engage in a greater diversity of behaviors. These experiences may, in turn, enhance cognitive functioning. This study examined associations between activity diversity and cognitive functioning across adulthood. Method Activity diversity was defined as the breadth and evenness of participation in seven common daily activity domains (e.g., paid work, time with children, leisure, physical activities, volunteering). Participants from the National Survey of Daily Experiences (NSDE: N = 732, Mage = 56) provided activity data during eight consecutive days at Wave 1 (W1) and Wave 2 (W2) 10 years apart. They also provided cognitive data at W2. Results Greater activity diversity at W2 was associated with higher overall cognitive functioning and higher executive functioning at W2. Individuals who increased activity diversity from W1 to W2 also exhibited higher scores in overall cognitive functioning and executive functioning at W2. Overall cognitive functioning, executive functioning, and episodic memory were better in those who had higher activity diversity at both waves, or increased activity diversity from W1 to W2, compared to those who had lower activity diversity or decreased activity diversity over time. Discussion Activity diversity is important for cognitive health in adulthood. Future work can study the directionality between activity diversity and cognitive functioning and underlying social and neurological mechanisms for these associations.

scholarly journals Inferring brain-computational mechanisms with models of activity measurements

2016 ◽  
Vol 371 (1705) ◽  
pp. 20160278 ◽  
Author(s):  
Nikolaus Kriegeskorte ◽  
Jörn Diedrichsen
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Summary Statistics ◽  
Activity Data ◽  
Individual Measurement ◽  
Activity Measurements ◽  
The Brain ◽  
The Way

High-resolution functional imaging is providing increasingly rich measurements of brain activity in animals and humans. A major challenge is to leverage such data to gain insight into the brain's computational mechanisms. The first step is to define candidate brain-computational models (BCMs) that can perform the behavioural task in question. We would then like to infer which of the candidate BCMs best accounts for measured brain-activity data. Here we describe a method that complements each BCM by a measurement model (MM), which simulates the way the brain-activity measurements reflect neuronal activity (e.g. local averaging in functional magnetic resonance imaging (fMRI) voxels or sparse sampling in array recordings). The resulting generative model (BCM-MM) produces simulated measurements. To avoid having to fit the MM to predict each individual measurement channel of the brain-activity data, we compare the measured and predicted data at the level of summary statistics. We describe a novel particular implementation of this approach, called probabilistic representational similarity analysis (pRSA) with MMs, which uses representational dissimilarity matrices (RDMs) as the summary statistics. We validate this method by simulations of fMRI measurements (locally averaging voxels) based on a deep convolutional neural network for visual object recognition. Results indicate that the way the measurements sample the activity patterns strongly affects the apparent representational dissimilarities. However, modelling of the measurement process can account for these effects, and different BCMs remain distinguishable even under substantial noise. The pRSA method enables us to perform Bayesian inference on the set of BCMs and to recognize the data-generating model in each case. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

Mortal Body, Immortal Mind

2012 ◽  
Vol 17 (1) ◽  
pp. 5-26
Author(s):  
Hans Goller
Keyword(s):  
Brain Activity ◽  
The Body ◽  
Activity Data ◽  
Brain Functions ◽  
Body Experiences ◽  
Research Findings ◽  
The Relationship ◽  
Near Death Experiences ◽  
The Brain ◽  
Alternative Theories

Neuroscientists keep telling us that the brain produces consciousness and consciousness does not survive brain death because it ceases when brain activity ceases. Research findings on near-death-experiences during cardiac arrest contradict this widely held conviction. They raise perplexing questions with regard to our current understanding of the relationship between consciousness and brain functions. Reports on veridical perceptions during out-of-body experiences suggest that consciousness may be experienced independently of a functioning brain and that self-consciousness may continue even after the termination of brain activity. Data on studies of near-death-experiences could be an incentive to develop alternative theories of the body-mind relation as seen in contemporary neuroscience.

“Grammar box” in the brain

2003 ◽  
Vol 26 (6) ◽  
pp. 672-673
Author(s):  
Valéria Csépe
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Neural Correlates ◽  
Modular Architecture ◽  
Activity Data ◽  
The Brain ◽  
Semantic Domains

Brain activity data prove the existence of qualitatively different structures in the brain. However, the question is whether the human brain acts as linguists assume in their models. The modular architecture of grammar that has been claimed by many linguists raises some empirical questions. One of the main questions is whether the threefold abstract partition of language (into syntactic, phonological, and semantic domains) has distinct neural correlates.

The Prognosis in Insanity

1883 ◽  
Vol 29 (126) ◽  
pp. 188-205
Author(s):  
D. G. Thomson
Keyword(s):  
Complete Resolution ◽  
Brain Activity ◽  
The State ◽  
Point Of View ◽  
Whole Brain ◽  
Increased Activity ◽  
The Brain ◽  
Abnormal Tissue

Mental Exaltation, Mania.—The question of the Prognosis in Mental Exaltation—Mania—in its various forms, is a far more debatable and uncertain matter than in melancholia. The symptoms in melancholia being of a negative character due to a lowering or suspension of brain activity, we do not look for all those diversities, endless varieties and aspects which we may find in mania, be it simple, acute, or chronic. Generally there is an increased vitality, a state of hyperæsthesia, an increase in the activity of the brain, generally of the whole brain, and we must believe that these states will not so easily end in complete resolution as the condition of merely depressed action, or rather no action, which obtains in melancholia—I mean in melancholia generally, and not those states of acute melancholia which are supposed to be closely allied to the state which in other brains and under other subjective circumstances would give rise to mania from a pathological point of view. If this increased activity does not rapidly terminate in resolution, one of two things must occur—either exhaustion or atrophy, resulting in death or dementia, will supervene, or abnormal tissue will invade or replace healthy nerve paths or areas, and chronic aberration of mind ensue.

scholarly journals Dissociating Neural Correlates of Action Monitoring and Metacognition of Agency

2011 ◽  
Vol 23 (11) ◽  
pp. 3620-3636 ◽  
Author(s):  
David B. Miele ◽  
Tor D. Wager ◽  
Jason P. Mitchell ◽  
Janet Metcalfe
Keyword(s):  
Brain Activity ◽  
Dorsal Striatum ◽  
Neural Correlates ◽  
Action Monitoring ◽  
Fmri Study ◽  
Metacognitive Judgments ◽  
The Right ◽  
Reflective Processing ◽  
Increased Activity ◽  
The Brain

Judgments of agency refer to people's self-reflective assessments concerning their own control: their assessments of the extent to which they themselves are responsible for an action. These self-reflective metacognitive judgments can be distinguished from action monitoring, which involves the detection of the divergence (or lack of divergence) between observed states and expected states. Presumably, people form judgments of agency by metacognitively reflecting on the output of their action monitoring and then consciously inferring the extent to which they caused the action in question. Although a number of previous imaging studies have been directed at action monitoring, none have assessed judgments of agency as a potentially separate process. The present fMRI study used an agency paradigm that not only allowed us to examine the brain activity associated with action monitoring but that also enabled us to investigate those regions associated with metacognition of agency. Regarding action monitoring, we found that being “out of control” during the task (i.e., detection of a discrepancy between observed and expected states) was associated with increased brain activity in the right TPJ, whereas being “in control” was associated with increased activity in the pre-SMA, rostral cingulate zone, and dorsal striatum (regions linked to self-initiated action). In contrast, when participants made self-reflective metacognitive judgments about the extent of their own control (i.e., judgments of agency) compared with when they made judgments that were not about control (i.e., judgments of performance), increased activity was observed in the anterior PFC, a region associated with self-reflective processing. These results indicate that action monitoring is dissociable from people's conscious self-attributions of control.

Peripheral endotoxin causes long-lasting changes in locus coeruleus activity via IL-1 in the brain

2002 ◽  
Vol 14 (6) ◽  
pp. 303-321 ◽  
Author(s):  
Mark K. Borsody ◽  
Jay M. Weiss
Keyword(s):  
Locus Coeruleus ◽  
Bacterial Infections ◽  
Low Dose ◽  
Brain Activity ◽  
Interleukin 1 ◽  
Gram Positive Bacteria ◽  
Polycytidylic Acid ◽  
Increased Activity ◽  
The Brain ◽  
Stimulation Of

Activity of locus coeruleus (LC) neurons, the major noradrenergic cell-body group in the brain whose axons give rise to approximately 70% of norepinephrine (NE) in the brain, is believed to play an important role in attention/vigilance, cognitive functions and behavioral disorders, particularly depression. Results described here show that in the rat, intraperitoneal (i.p.) injection of lipopolysaccharide (LPS, a bacterial endotoxin) causes long-lasting changes in electrophysiological activity of LC neurons that are mediated by interleukin-1 (IL-1) acting locally in the LC region. First, it was found that IL-1, when microinjected into the LC region or stimulated/expressed in that brain region, increased activity of LC neurons. The only exception to this was that a very low dose of microinjected IL-1 (5 pg) decreased LC activity, which could be blocked by an antagonist to corticotropin-releasing hormone (CRH), thus suggesting that the decrease was due to IL-1 stimulation of CRH release. All of these effects could be blocked by injection and/or infusion of IL-1 receptor antagonist (IL-1RA) specifically into the LC region. Next, intraperitoneal (i.p.) injection of a low dose of LPS(10 µg/kg or 100 ng/kg) was also found to increase LC activity. The excitation of LC produced by 10 µg/kg i.p. LPS increased progressively for at least 1 week, with LC neurons firing at more than twice their normal rate at 1 week after the i.p. LPS injection. Alteration of LC activity lasted for 3 weeks after a single i.p. injection of 10 µg/kg LPS. The effects of i.p. LPS on LC activity at any time after i.p. injection could be blocked by a brief microinfusion of IL-1RA into the LC region, thereby indicating that changes in LC activity seen after the i.p. LPS were caused by IL-1 acting in the LC region. Finally, i.p. injection of peptidoglycan, representing gram-positive bacteria, and polyinsinic-polycytidylic acid [poly(I):(C)], representing viral infection, also caused increases in LC activity, and the effects of peptidoglycan [but not those of poly(I):(C)] were blocked by microinfusion of IL-1RA into LC. These findings suggest that bacterial infections can give rise to prolonged changes in brain activity through cytokine action in brain.

A Neurobiological Account of False Memories

2017 ◽  
Author(s):  
Vincent van de Ven ◽  
Henry Otgaar ◽  
Mark L. Howe
Keyword(s):  
Executive Functioning ◽  
Medial Temporal Lobe ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
False Memories ◽  
Mental States ◽  
Memory Formation ◽  
Memory Encoding ◽  
Associative Account ◽  
The Brain

This chapter discusses human functional neuroimaging findings about how the brain creates true and false memories. These studies have shown that different brain systems contribute to the creation and retrieval of false memories, including systems for sensory perception, executive functioning and cognitive control, and the medial temporal lobe, which has long been associated with episodic and autobiographical memory formation. Many neuroimaging findings provide support for an associative account of false memories, which proposes that false memories arise from associating unrelated mental experiences in memory. At the same time, other neuroimaging findings suggest that false memory creation may depend on states of brain activity during memory encoding. Finally, the chapter briefly provides cautionary notes about using functional neuroimaging as a tool to assess private mental states in individual cases in the courtroom.

scholarly journals Constructing Brain Connectivity Model Using Causal Network Reconstruction Approach

2021 ◽  
Vol 15 ◽  
Author(s):  
Supat Saetia ◽  
Natsue Yoshimura ◽  
Yasuharu Koike
Keyword(s):  
Causal Effect ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Activity Data ◽  
Pairwise Correlation ◽  
Brain Functions ◽  
Human Connectome Project ◽  
Graphical Tool ◽  
Connectivity Model ◽  
The Brain

Studying brain function is a challenging task. In the past, we could only study brain anatomical structures post-mortem, or infer brain functions from clinical data of patients with a brain injury. Nowadays technology, such as functional magnetic resonance imaging (fMRI), enable non-invasive brain activity observation. Several approaches have been proposed to interpret brain activity data. The brain connectivity model is a graphical tool that represents the interaction between brain regions, during certain states. It depicts how a brain region cause changes to other parts of the brain, which can be implied as information flow. This model can be used to help interpret how the brain works. There are several mathematical frameworks that can be used to infer the connectivity model from brain activity signals. Granger causality is one such approach and is one of the first that has been applied to brain activity data. However, due to the concept of the framework, such as the use of pairwise correlation, combined with the limitation of brain activity data such as low temporal resolution in case of fMRI signal, makes the interpretation of the connectivity difficult. We therefore propose the application of the Tigramite causal discovery framework on fMRI data. The Tigramite framework uses measures such as causal effect to analyze causal relations in the system. This enables the framework to identify both direct and indirect pathways or connectivities. In this paper, we applied the framework to the Human Connectome Project motor task-fMRI dataset. We then present the results and discuss how the framework improves interpretability of the connectivity model. We hope that this framework will help us understand more complex brain functions such as memory, consciousness, or the resting-state of the brain, in the future.

scholarly journals Measurement of Brain Activity Rate Based on Electroensefalographical Signals on Smokers

2018 ◽  
Vol 3 (1) ◽  
pp. 15
Author(s):  
Herry Setiawan
Keyword(s):  
Brain Activity ◽  
Ion Current ◽  
Sampled Data ◽  
Voltage Difference ◽  
The Third ◽  
China And India ◽  
Level Information ◽  
Increased Activity ◽  
The Brain ◽  
Continue Smoking

Indonesia as a country with 255,182,144 people (Central Bureau of Statistics, 2015) with the number of smokers reached 46.16 percent in the third rank with the largest number of smokers in the world after China and India, there are some elements in cigarettes one of them is nicotine, it will be one of the addictive additives. It's why smokers want to continue smoking cigarettes on a regular basis. It bounds to the brain receptors and in other organs. Increased activity in the orbitofrontal area of the cortex occurs when a smoker wants a cigarette, while in the prefrontal cortex experiences an increase in activity when smokers smoke cigarettes. Increased activity in the area will produce electrically along the scalp that can be measured using Electroencephalography (EEG). The voltage difference of the ion current will give the addiction level information to the cigarette so it can be classified. Classification is done in 4 classes namely low dependence, Moderate dependence and high dependence. From the results of the study we found that the level of brain activity of the frontal cortex increased. 52% of the 40 sampled data showed the highest increase in activity by reaching 53.17% in the highly dependent addiction category.

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

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