scholarly journals Excitatory TMS Boosts Memory Representations

2018 ◽  
Author(s):  
Wei-Chun Wang ◽  
Erik A. Wing ◽  
David L.K. Murphy ◽  
Bruce M. Luber ◽  
Sarah H. Lisanby ◽  
...  
Keyword(s):  
Cognitive Enhancement ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Neural Mechanisms ◽  
Temporal Memory ◽  
Memory Functioning ◽  
Neural Representations ◽  
Memory Representations ◽  
Science Investigations ◽  
Univariate Analyses

AbstractBrain stimulation technologies have seen increasing application in basic science investigations, specifically towards the goal of improving memory functioning. However, proposals concerning the neural mechanisms underlying cognitive enhancement often rely on simplified notions of excitation and, most applications examining the effects of transcranial magnetic stimulation (TMS) on functional neuroimaging measures have been limited to univariate analyses of brain activity. We present here analyses using representational similarity analysis (RSA) and encoding-retrieval similarity (ERS) analysis in order to quantify the effect of TMS on memory representations. To test whether an increase in local excitability in PFC can have measurable influences on upstream representations in earlier temporal memory regions, we compared 1Hz and 5Hz stimulation to the left dorsolateral PFC. We found that 10 minutes of 5Hz rTMS, relative to 1Hz, had multiple effects on neural representations: 1) greater RSA during both encoding and retrieval, 2) greater ERS across all items, and, critically, 3) increasing ERS in MTL with increasing univariate activity in DLPFC, and greater functional connectivity for hits than misses between these regions. These results provide the first evidence of rTMS enhancing semantic representations and strengthen the idea that rTMS may affect the reinstatement of previously experienced events in upstream regions.

scholarly journals Functional neuroimaging studies of the effects of psychotherapy

2014 ◽  
Vol 16 (1) ◽  
pp. 75-81 ◽  
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Behavioral Changes ◽  
Neural Mechanisms ◽  
Psychological Interventions ◽  
Emotional States ◽  
Major Depressive ◽  
Psychotherapeutic Interventions ◽  
Functional Brain Activity ◽  
Neuroimaging Techniques

It has been long established that psychological interventions can markedly alter patients' thinking patterns, beliefs, attitudes, emotional states, and behaviors. Little was known about the neural mechanisms mediating such alterations before the advent of functional neuroimaging techniques. Since the turn of the new millenium, several functional neuroimaging studies have been conducted to tackle this important issue. Some of these studies have explored the neural impact of various forms of psychotherapy in individuals with major depressive disorder. Other neuroimaging studies have investigated the effects of psychological interventions for anxiety disorders. I review these studies in the present article, and discuss the putative neural mechanisms of change in psychotherapy. The findings of these studies suggest that mental and behavioral changes occurring during psychotherapeutic interventions can lead to a normalization of functional brain activity at a global level.

Theoretical, Statistical, and Practical Perspectives on Pattern-based Classification Approaches to the Analysis of Functional Neuroimaging Data

2007 ◽  
Vol 19 (11) ◽  
pp. 1735-1752 ◽  
Author(s):  
Alice J. O'Toole ◽  
Fang Jiang ◽  
Hervé Abdi ◽  
Nils Pénard ◽  
Joseph P. Dunlop ◽  
...  
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Point Of View ◽  
Experimental Conditions ◽  
Theoretical Terms ◽  
Activation Patterns ◽  
Neural Representations ◽  
The Status ◽  
Neuroimaging Data

The goal of pattern-based classification of functional neuroimaging data is to link individual brain activation patterns to the experimental conditions experienced during the scans. These “brain-reading” analyses advance functional neuroimaging on three fronts. From a technical standpoint, pattern-based classifiers overcome fatal f laws in the status quo inferential and exploratory multivariate approaches by combining pattern-based analyses with a direct link to experimental variables. In theoretical terms, the results that emerge from pattern-based classifiers can offer insight into the nature of neural representations. This shifts the emphasis in functional neuroimaging studies away from localizing brain activity toward understanding how patterns of brain activity encode information. From a practical point of view, pattern-based classifiers are already well established and understood in many areas of cognitive science. These tools are familiar to many researchers and provide a quantitatively sound and qualitatively satisfying answer to most questions addressed in functional neuroimaging studies. Here, we examine the theoretical, statistical, and practical underpinnings of pattern-based classification approaches to functional neuroimaging analyses. Pattern-based classification analyses are well positioned to become the standard approach to analyzing functional neuroimaging data.

Inhibitory and monitoring cortical networks during conversion and hypnotic paralysis in FMRI

2011 ◽  
Vol 26 (S2) ◽  
pp. 2155-2155
Author(s):  
Y. cojan ◽  
L. Waber ◽  
A. Forster ◽  
P. Vuilleumier
Keyword(s):  
Psychiatric Disorders ◽  
Inhibitory Control ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Human Mind ◽  
Neural Mechanisms ◽  
Self Control ◽  
Abnormal Behaviour ◽  
Brain Functions ◽  
Cognitive Theories

Hypnosis may induce striking changes in consciousness and volition under the effect of particular suggestions. Popular theories often consider hypnosis as a state of consciousness where volition is abolished, while cognitive theories postulate that it involves inhibitory control processes mediated by frontal lobe areas. Moreover, since the time of Freud and Charcot, hypnotic effects have often been likened to the abnormal behaviour seen in some psychiatric disorders such as hysteria. However, the neural mechanisms of these different conditions and their putative relationships still remain unclear. By using functional neuroimaging methods in volunteers and patient, we can now identify specific changes in brain activity that underlie the behavioural and perceptual alterations observed during hypnosis and directly compare the latter with findings in hysteria conversion. Our recent results suggest both commonalities between these two conditions, as suggested by Freud and Charcot, but also clear differences that are consistent modern views on hysteria and brain functions. Moreover, hypnosis appears to reflect a state of heightened self-control and monitoring, in agreement with some cognitive theories. This research does not only provide novel insights on how the human mind can regulate itself, but also help better understand the neural underpinning of hysteria, a condition standing at the frontiers of psychiatry and neurology since more than a century.

scholarly journals Neuro-Computational Foundations of Moral Preferences

2019 ◽  
Author(s):  
Giuseppe Ugazio ◽  
Marcus Grueschow ◽  
Rafael Polania ◽  
Claus Lamm ◽  
Philippe N. Tobler ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Human Life ◽  
Neural Mechanisms ◽  
Common Currency ◽  
Moral Value ◽  
Neural Representations ◽  
Behavioral Paradigm ◽  
The Common ◽  
Decision Mechanisms

AbstractMoral preferences pervade many aspects of our lives, dictating how we ought to behave, whom we can marry, and even what we eat. Despite their relevance, one fundamental question remains unanswered: Where do individual moral preferences come from? It is often thought that all types of preferences reflect properties of domain-general neural decision mechanisms that employ a common “neural currency” to value choice options in many different contexts. This assumption, however, appears at odds with the observation that many humans consider it intuitively wrong to employ the same scale to compare moral value (e.g., of a human life) with material value (e.g., of money). In this paper, we directly challenge the common-currency hypothesis by comparing the neural mechanisms that represent moral and financial subjective values. In a study combining fMRI with a novel behavioral paradigm, we identify neural representations of the subjective values of human lives or financial payoffs by means of structurally identical computational models. Correlating isomorphic model variables from both domains with brain activity reveals specific patterns of neural activity that selectively represent values in the moral (in the rTPJ) or financial (in the vmPFC) domain. Thus, our findings show that human lives and money are valued in distinct neural currencies, supporting theoretical proposals that human moral behavior is guided by processes that are distinct from those underlying behavior driven by personal material benefit.

Behavior in the Brain

2010 ◽  
Vol 24 (2) ◽  
pp. 76-82 ◽  
Author(s):  
Martin M. Monti ◽  
Adrian M. Owen
Keyword(s):  
Motor Behavior ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Motor Output ◽  
The Unconscious ◽  
Ethical Implications ◽  
Brain Responses ◽  
Minimally Conscious ◽  
Brain Insults ◽  
Brain Behavior

Recent evidence has suggested that functional neuroimaging may play a crucial role in assessing residual cognition and awareness in brain injury survivors. In particular, brain insults that compromise the patient’s ability to produce motor output may render standard clinical testing ineffective. Indeed, if patients were aware but unable to signal so via motor behavior, they would be impossible to distinguish, at the bedside, from vegetative patients. Considering the alarming rate with which minimally conscious patients are misdiagnosed as vegetative, and the severe medical, legal, and ethical implications of such decisions, novel tools are urgently required to complement current clinical-assessment protocols. Functional neuroimaging may be particularly suited to this aim by providing a window on brain function without requiring patients to produce any motor output. Specifically, the possibility of detecting signs of willful behavior by directly observing brain activity (i.e., “brain behavior”), rather than motoric output, allows this approach to reach beyond what is observable at the bedside with standard clinical assessments. In addition, several neuroimaging studies have already highlighted neuroimaging protocols that can distinguish automatic brain responses from willful brain activity, making it possible to employ willful brain activations as an index of awareness. Certainly, neuroimaging in patient populations faces some theoretical and experimental difficulties, but willful, task-dependent, brain activation may be the only way to discriminate the conscious, but immobile, patient from the unconscious one.

scholarly journals Delta band activity contributes to the identification of command following in disorder of consciousness

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gonzalo Rivera-Lillo ◽  
Emmanuel A. Stamatakis ◽  
Tristan A. Bekinschtein ◽  
David K. Menon ◽  
Srivas Chennu
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Disorder Of Consciousness ◽  
Fine Grained ◽  
Electrical Brain Activity ◽  
Delta Band ◽  
Delta Modulation ◽  
Command Following ◽  
Band Activity

AbstractThe overt or covert ability to follow commands in patients with disorders of consciousness is considered a sign of awareness and has recently been defined as cortically mediated behaviour. Despite its clinical relevance, the brain signatures of the perceptual processing supporting command following have been elusive. This multimodal study investigates the temporal spectral pattern of electrical brain activity to identify features that differentiated healthy controls from patients both able and unable to follow commands. We combined evidence from behavioural assessment, functional neuroimaging during mental imagery and high-density electroencephalography collected during auditory prediction, from 21 patients and 10 controls. We used a penalised regression model to identify command following using features from electroencephalography. We identified seven well-defined spatiotemporal signatures in the delta, theta and alpha bands that together contribute to identify DoC subjects with and without the ability to follow command, and further distinguished these groups of patients from controls. A fine-grained analysis of these seven signatures enabled us to determine that increased delta modulation at the frontal sensors was the main feature in command following patients. In contrast, higher frequency theta and alpha modulations differentiated controls from both groups of patients. Our findings highlight a key role of spatiotemporally specific delta modulation in supporting cortically mediated behaviour including the ability to follow command. However, patients able to follow commands nevertheless have marked differences in brain activity in comparison with healthy volunteers.

scholarly journals Neural alignment predicts learning outcomes in students taking an introduction to computer science course

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Meir Meshulam ◽  
Liat Hasenfratz ◽  
Hanna Hillman ◽  
Yun-Fei Liu ◽  
Mai Nguyen ◽  
...  
Keyword(s):  
Computer Science ◽  
Learning Outcomes ◽  
Brain Activity ◽  
Activity Patterns ◽  
Real Life ◽  
Final Exam ◽  
Neural Representations ◽  
Real Life Setting ◽  
The Right ◽  
Mri Study

AbstractDespite major advances in measuring human brain activity during and after educational experiences, it is unclear how learners internalize new content, especially in real-life and online settings. In this work, we introduce a neural approach to predicting and assessing learning outcomes in a real-life setting. Our approach hinges on the idea that successful learning involves forming the right set of neural representations, which are captured in canonical activity patterns shared across individuals. Specifically, we hypothesized that learning is mirrored in neural alignment: the degree to which an individual learner’s neural representations match those of experts, as well as those of other learners. We tested this hypothesis in a longitudinal functional MRI study that regularly scanned college students enrolled in an introduction to computer science course. We additionally scanned graduate student experts in computer science. We show that alignment among students successfully predicts overall performance in a final exam. Furthermore, within individual students, we find better learning outcomes for concepts that evoke better alignment with experts and with other students, revealing neural patterns associated with specific learned concepts in individuals.

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