Publications by authors named "J R Fincham"

255 Publications

Negative Consequences of the Widespread and Inappropriate Easy Access to Purchasing Prescription Medications on the Internet.

Jack E Fincham

Am Health Drug Benefits 2021 Mar;14(1):22-28

Professor, Osher Lifelong Learning Institute, University of Arizona, and Dean Emeritus, University of Kansas School of Pharmacy, Tucson, AZ.

Background: The purchase of prescription medications via the Internet is a global phenomenon with significant economic, social, and health-related impacts. The growth of online purchasing of prescription medicines is significant and has been amplified by social isolation related to the COVID-19 pandemic, with many patients unable to obtain medicines as they normally would. By contrast, there are licensed, certified, legitimate retail pharmacies that provide significant and vital services to patients.

Objective: To review the major public health threat from illegal entities that sell any type of prescription medicines to individuals without proper physician oversight.

Discussion: Rogue and inappropriate online vendors are providing counterfeit and substandard medications fraudulently with untold impacts on morbidity and mortality globally. This article presents the differentiation between the types of legal and illegal Internet pharmacies, as well as the actions that are currently in play to affect the illegal online purchase of prescription medicines. Much must be done in a collaborative, global effort to address the public health threat of obtaining prescription drugs via the Internet.

Conclusion: Global, federal, state, health professional, societal, and patient-specific collaborations are necessary to affect the significant threat that is now present via the increasing ease of access to online medication purchases.
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March 2021

Reconstructing fine-grained cognition from brain activity.

Neuroimage 2020 11 1;221:116999. Epub 2020 Jun 1.

The Rand Corporation, United States.

We describe the Sketch-and-Stitch method for bringing together a cognitive model and EEG to reconstruct the cognition of a subject. The method was tested in the context of a video game where the actions are highly interdependent and variable: simply changing whether a key was pressed or not for a 30th of a second can lead to a very different outcome. The Sketch level identifies the critical events in the game and the Stitch level fills in the detailed actions between these events. The critical events tend to produce robust EEG signals and the cognitive model provides probabilities of various transitions between critical events and the distribution of intervals between these events. This information can be combined in a hidden semi-Markov model that identifies the most probable sequence of critical events and when they happened. The Stitch level selects detailed actions from an extensive library of model games to produce these critical events. The decision about which sequence of actions to select from the library is made on the basis of how well they would produce weaker aspects of the EEG signal. The resulting approach can produce quite compelling replays of actual games from the EEG of a subject.
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November 2020

Spatiotemporal analysis of event-related fMRI to reveal cognitive states.

Hum Brain Mapp 2020 02 14;41(3):666-683. Epub 2019 Nov 14.

Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania.

Cognitive science has a rich history of developing theories of processing that characterize the mental steps involved in performance of many tasks. Recent work in neuroimaging and machine learning has greatly improved our ability to link cognitive processes with what is happening in the brain. This article analyzes a hidden semi-Markov model-multivoxel pattern-analysis (HSMM-MVPA) methodology that we have developed for inferring the sequence of brain states one traverses in the performance of a cognitive task. The method is applied to a functional magnetic resonance imaging (fMRI) experiment where task boundaries are known that should separate states. The method is able to accurately identify those boundaries. Then, applying the method to synthetic data, we explore more fully those factors that influence performance of the method: signal-to-noise ratio, numbers of states, state sojourn times, and numbers of underlying experimental conditions. The results indicate the types of experimental tasks where applications of the HSMM-MVPA method are likely to yield accurate and insightful results.
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February 2020

The Common Time Course of Memory Processes Revealed.

Psychol Sci 2018 09 10;29(9):1463-1474. Epub 2018 Jul 10.

4 Machine Learning Department, Carnegie Mellon University.

Magnetoencephalography (MEG) was used to compare memory processes in two experiments, one involving recognition of word pairs and the other involving recall of newly learned arithmetic facts. A combination of hidden semi-Markov models and multivariate pattern analysis was used to locate brief "bumps" in the sensor data that marked the onset of different stages of cognitive processing. These bumps identified a separation between a retrieval stage that identified relevant information in memory and a decision stage that determined what response was implied by that information. The encoding, retrieval, decision, and response stages displayed striking similarities across the two experiments in their duration and brain activation patterns. Retrieval and decision processes involve distinct brain activation patterns. We conclude that memory processes for two different tasks, associative recognition versus arithmetic retrieval, follow a common spatiotemporal neural pattern and that both tasks have distinct retrieval and decision stages.
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September 2018

Cannabis for Chronic Pain: Challenges and Considerations.

Pharmacotherapy 2018 06 16;38(6):651-662. Epub 2018 May 16.

Department of Anesthesiology, Pain Mechanisms Laboratory, Wake Forest University School of Medicine, Winston-Salem, North Carolina.

The National Academies of Sciences, Engineering, and Medicine has found substantial evidence that cannabis (plant) is effective for the treatment of chronic pain in adults, and moderate evidence that oromucosal cannabinoids (extracts, especially nabiximols) improve short-term sleep disturbances in chronic pain. The paradoxical superiority of the cannabis plant over cannabinoid molecules represents a challenge for the medical community and the established processes that define modern pharmacy. The expanding and variable legalization of cannabis in multiple states nationwide represents an additional challenge for patients and the medical community because recreational and medicinal cannabis are irresponsibly overlapped. Cannabis designed for recreational use (containing high levels of active ingredients) is increasingly available to patients with chronic pain who do not find relief with current pharmacologic entities, which exposes patients to potential harm. This article analyzes the available scientific evidence to address controversial questions that the current state of cannabis poses for health care professionals and chronic pain patients and sets the basis for a more open discussion about the role of cannabis in modern medicine for pain management. A critical discussion on these points, the legal status of cannabis, and considerations for health care providers is presented.
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June 2018