Brain imaging and courtroom evidence: on the admissibility and persuasiveness of fMRI

2006 ◽  
Vol 2 (3) ◽  
pp. 233-255 ◽  
Author(s):  
Neal Feigenson
Keyword(s):  
Magnetic Resonance Imaging ◽  
Expert Testimony ◽  
Brain Function ◽  
Functional Neuroimaging ◽  
Mental States ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Advanced Technique ◽  
Probative Value ◽  
Shed Light

Functional magnetic resonance imaging (fMRI) is currently the most advanced technique for measuring and depicting brain function. Functional MRI studies abound in neuroscience, psychiatry and psychology. Inevitably, fMRI-based evidence will be offered in court as proof of matters involving parties’ mental states and capabilities. This paper analyses the likely admissibility of fMRI testimony and images. Cases involving other types of functional neuroimaging (PET and SPECT), which may shed light on judges’ receptivity to fMRI evidence, are briefly surveyed. The conceptual and methodological underpinnings of fMRI are then explored, prompting basic questions about the evidentiary reliability and relevance of fMRI results. The first reported case involving fMRI evidence, which raises several of these questions, is described. Finally, the admissibility and probative value of the fMRI images themselves are discussed. Assuming that the expert testimony that the images are offered to illustrate is admissible, it is argued that the law can obtain the benefits of fMRI science while minimising the judgmental risks by allowing triers of fact to see the images and encouraging experts and lawyers to educate the triers to interpret the images properly.

scholarly journals Perceiving actions before they happen: psychological dimensions scaffold neural action prediction

2020 ◽  
Author(s):  
Mark A Thornton ◽  
Diana I Tamir
Keyword(s):  
Magnetic Resonance Imaging ◽  
Functional Neuroimaging ◽  
Social World ◽  
Action Space ◽  
Action Prediction ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
The Social ◽  
Psychological Dimensions ◽  
The Brain

Abstract The social world buzzes with action. People constantly walk, talk, eat, work, play, snooze and so on. To interact with others successfully, we need to both understand their current actions and predict their future actions. Here we used functional neuroimaging to test the hypothesis that people do both at the same time: when the brain perceives an action, it simultaneously encodes likely future actions. Specifically, we hypothesized that the brain represents perceived actions using a map that encodes which actions will occur next: the six-dimensional Abstraction, Creation, Tradition, Food(-relevance), Animacy and Spiritualism Taxonomy (ACT-FAST) action space. Within this space, the closer two actions are, the more likely they are to precede or follow each other. To test this hypothesis, participants watched a video featuring naturalistic sequences of actions while undergoing functional magnetic resonance imaging (fMRI) scanning. We first use a decoding model to demonstrate that the brain uses ACT-FAST to represent current actions. We then successfully predicted as-yet unseen actions, up to three actions into the future, based on their proximity to the current action’s coordinates in ACT-FAST space. This finding suggests that the brain represents actions using a six-dimensional action space that gives people an automatic glimpse of future actions.

scholarly journals Hierarchical Spatio-Temporal Modeling of Naturalistic Functional Magnetic Resonance Imaging Signals via Two-Stage Deep Belief Network With Neural Architecture Search

2021 ◽  
Vol 15 ◽  
Author(s):  
Yudan Ren ◽  
Shuhan Xu ◽  
Zeyang Tao ◽  
Limei Song ◽  
Xiaowei He
Keyword(s):  
Magnetic Resonance Imaging ◽  
Deep Learning ◽  
Magnetic Resonance ◽  
Brain Function ◽  
Learning Models ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Two Stage ◽  
Functional Activities ◽  
Neural Architecture

Naturalistic functional magnetic resonance imaging (NfMRI) has become an effective tool to study brain functional activities in real-life context, which reduces the anxiety or boredom due to difficult or repetitive tasks and avoids the problem of unreliable collection of brain activity caused by the subjects’ microsleeps during resting state. Recent studies have made efforts on characterizing the brain’s hierarchical organizations from fMRI data by various deep learning models. However, most of those models have ignored the properties of group-wise consistency and inter-subject difference in brain function under naturalistic paradigm. Another critical issue is how to determine the optimal neural architecture of deep learning models, as manual design of neural architecture is time-consuming and less reliable. To tackle these problems, we proposed a two-stage deep belief network (DBN) with neural architecture search (NAS) combined framework (two-stage NAS-DBN) to model both the group-consistent and individual-specific naturalistic functional brain networks (FBNs), which reflected the hierarchical organization of brain function and the nature of brain functional activities under naturalistic paradigm. Moreover, the test-retest reliability and spatial overlap rate of the FBNs identified by our model reveal better performance than that of widely used traditional methods. In general, our model provides a promising method for characterizing hierarchical spatiotemporal features under the natural paradigm.

scholarly journals IMAGING IN ENDOCRINOLOGY: The use of functional MRI to study the endocrinology of appetite

2015 ◽  
Vol 173 (2) ◽  
pp. R59-R68 ◽  
Author(s):  
Victoria Salem ◽  
Waljit S Dhillo
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Feeding Behaviour ◽  
Review Article ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Current Thinking ◽  
Reward Value ◽  
The Brain ◽  
Shed Light

In the present review article, we summarise current thinking about the neuroendocrinology of appetite and feeding behaviour. We discuss how the homeostatic control of energy balance, wherein the hypothalamus orchestrates food intake and energy expenditure in response to peripheral signals about nutritional status, can be easily overridden by the powerful reward value of food. We focus on how functional magnetic resonance imaging has shed light on our understanding of the way hormones can interact with the brain to modulate appetite.

scholarly journals Image Features of Resting-State Functional Magnetic Resonance Imaging in Evaluating Poor Emotion and Sleep Quality in Patients with Chronic Pain under Artificial Intelligence Algorithm

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Shuqin Yang ◽  
Xiaoyan Bie ◽  
Yanmei Wang ◽  
Junnan Li ◽  
Yujing Wang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Chronic Pain ◽  
Sleep Quality ◽  
Resting State ◽  
Brain Function ◽  
Control Group ◽  
Observation Group ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
The Brain

The balanced iterative reducing and clustering using hierarchies (BIRCH) method was adopted to optimize the results of the resting-state functional magnetic resonance imaging (RS-fMRI) to analyze the changes in the brain function of patients with chronic pain accompanied by poor emotion or abnormal sleep quality in this study, so as to provide data support for the prevention and treatment of clinical chronic pain with poor emotion or sleep quality. 159 patients with chronic pain who visited the hospital were selected as the research objects, and they were grouped according to the presence or absence of abnormalities in emotion and sleep. The patients without poor emotion and sleep quality were set as the control group (60 cases), and the patients with the above symptoms were defined in the observation group (90 cases). The brain function was detected by RS-fMRI technology based on the BIRCH algorithm. The results showed that the rand index (RI), adjustment of RI (ARI), and Fowlkes–Mallows index (FMI) results in the k-means, flow cytometry (FCM), and BIRCH algorithms were 0.82, 0.71, and 0.88, respectively. The scores of Hamilton Depression Scale (HAHD), Hamilton Anxiety Scale (HAMA), and Pittsburgh Sleep Quality Index (PSQI) were 7.26 ± 3.95, 7.94 ± 3.15, and 8.03 ± 4.67 in the observation group and 4.03 ± 1.95, 5.13 ± 2.35, and 4.43 ± 2.07 in the control group; the higher proportion of RS-fMRI was with abnormal brain signal connections. A score of 7 or more meant that the number of brain abnormalities was more than 90% and that of less than 7 was less than 40%, showing a statistically obvious difference in contrast P < 0.05 . Therefore, the BIRCH clustering algorithm showed reliable value in the optimization of RS-fMRI images, and RS-fMRI showed high application value in evaluating the emotion and sleep quality of patients with chronic pain.

scholarly journals Resting-state functional magnetic resonance imaging of high altitude patients with obstructive sleep apnoea hypopnoea syndrome

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Zongyuan Qin ◽  
Dongjie Kang ◽  
Xiang Feng ◽  
Demin Kong ◽  
Fangfang Wang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
High Altitude ◽  
Resting State ◽  
Brain Function ◽  
Sleep Apnoea ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Obstructive Sleep ◽  
The Brain

Abstract The objective of the study was to observe brain function changes in Obstructive Sleep Apnoea Hypopnoea Syndrome (OSAHS) patients at high altitude. Resting-state functional magnetic resonance imaging (rs-fMRI) in patients with OSAHS was assessed using regional homogeneity (ReHo), amplitude of low frequency fluctuation (ALFF) and functional connectivity (FC). In this study, 36 male patients with OSAHS and 38 healthy male subjects were recruited from high-altitude areas, specifically, altitudes of 2,000–3,000 m. OSAHS was diagnosed by polysomnography (PSG). The blood oxygen level-dependent (BOLD) signals of OSAHS patients and healthy controls in the resting state were obtained and compared using ReHo, ALFF and FC methods. The posterior cingulate cortex (PCC) was selected as the seed region in the comparison of FC between the two groups. Compared with the healthy control group, multiple brain functions in the OSAHS patient group were different. There were correlations between the brain function values of some brain regions and demographic data. We also found that in contrast to earlier findings with individuals in plains areas, the brain function at the frontal lobe and the precuneus were higher in OSAHS patients, and the PCC showed higher FC with the left caudate, which may be due to the high-altitude hypoxic environment.

Neuropharmacological functional imaging

e-Neuroforum ◽  
2013 ◽  
Vol 19 (4) ◽  
Author(s):  
C. Thiel
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Neuroimaging ◽  
Methodological Approach ◽  
Animal Experiments ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Imaging Studies ◽  
Recent Developments ◽  
Research Findings

AbstractThe marriage of psychopharmacology with functional neuroimaging enables the investi­gation of neurochemical modulation of cognitive functions in the human brain. From the point of basic neurocognitive research, pharmacological functional neuroimaging is hence a valuable completion of animal experiments. From the point of clinical neuro­science, pharmacological neuroimaging con­tributes to the understanding and development of pharmacological treatment ap­proaches for patients with neurological and psychiatric disorders. The present paper prov­ides an overview of the methodological approach and illustrates research findings and recent developments from pharmacological functional magnetic resonance imaging studies by means of selective examples from the dopaminergic and cholinergic neurotrans­mitter system.

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