Of Reptiles and Velcro: The Brain\u27s Negativity Bias and Persuasion

Negative political advertising has become commonplace for one simple reason it works Cognitive pyschologists attribute this to a phenomenon they call the brain\u27s ÔÇ£negativity biasÔÇØ That is our brains are more apt to process and retain negative information as opposed to positive information As one neuropsychologist has put it ÔÇ£your brain is like Velcro for negative experiences and Teflon for positive onesÔÇØCognitive psychologists have concluded that bad stimuli have significantly more power across a broad range of psychological phenomena What are the implications of this finding for legal writing For example how do judges respond to negative themes in briefs Should lawyers phrase their legal arguments in terms of avoiding bad outcomes instead of promoting good outcomes Should rule statements in briefs highlight the possible negative consequences of a particular ruling as opposed to a positive outcome Should advocates adopt a negative or aggressive tone in their writing Does this finding change the way lawyers should do or at least think about counteranalysis Does a judge\u27s negative opinion of an advocate have more power than a potential positive view of the clientAnswering these questions in the affirmative might be controversial Many a judge as well as many legal writing professors counsel lawyers and law students to avoid the negative and emphasize the positive Given the near ubiquitousness of this advice it seems that the cognitive psychology on negativity bias is worth studying Have we all been giving bad advice all this time This article discusses the cognitive psychology findings then suggests some hypotheses for how they might inform choices that advocates might make It is intended to open a conversation about how the negativity bias might affect the process of persuasio

Wireless multi-channel sensor for neurodynamic studies

Journal ArticleThis paper presents the design of a bio-compatible, implantable neural recording device for Aplysia californica, a common sea slug. Low-voltage extracellular neural signals (<100 μV) are recorded using a high-performance, low-power, low-noise preamplifier that is integrated with programmable data acquisition and control, and FSK telemetry that provides 5-kbps wireless neural data through 18 cm of saltwater. The telemetry utilizes an 8-cm electric dipole antenna matched to 50 Ω by exposing the ends of the antenna to the saltwater. A 3-V lithium ion battery (160 mAh) allows 16 hours of recording. Neural data obtained using extracellular nerve electrodes and a wired interface to this device have 2.5-µVrms noise, comparable to commercial neural recording equipment

MacCrate (in)Action: The Case for Enhancing the Upper-Level Writing Requirement in Law Schools

In 2001, the American Bar Association amended the Standards for Accreditation of Law Schools to require, for the first time, a “rigorous writing experience after the first year.” During the summer of 2004 the author conducted a nationwide survey to determine how law schools responded to this change. The author found that most schools did little more than to require students to take at least one course which was evaluated by means of an academic paper rather than an examination. The author concludes that this is probably not the response the ABA had hoped for, but suggests that a 2005 amendment to the Standards, which now require “writing in a legal context”, holds more promise for encouraging law schools to focus more on practical legal writing skills

Fascicle localisation within peripheral nerves through evoked activity recordings: A comparison between electrical impedance tomography and multi-electrode arrays

BACKGROUND: The lack of understanding of fascicular organisation in peripheral nerves limits the potential of vagus nerve stimulation therapy. Two promising methods may be employed to identify the functional anatomy of fascicles within the nerve: fast neural electrical impedance tomography (EIT), and penetrating multi-electrode arrays (MEA). These could provide a means to image the compound action potential within fascicles in the nerve. NEW METHOD: We compared the ability to localise fascicle activity between silicon shanks (SS) and carbon fibre (CF) multi-electrode arrays and fast neural EIT, with micro-computed tomography (MicroCT) as an independent reference. Fast neural EIT in peripheral nerves was only recently developed and MEA technology has been used only sparingly in nerves and not for source localisation. Assessment was performed in rat sciatic nerves while evoking neural activity in the tibial and peroneal fascicles. RESULTS: Recorded compound action potentials were larger with CF compared to SS (∼700μV vs ∼300μV); however, background noise was greater (6.3μV vs 1.7μV) leading to lower SNR. Maximum spatial discrimination between Centres-of-Mass of fascicular activity was achieved by fast neural EIT (402±30μm) and CF MEA (414±123μm), with no statistical difference between MicroCT (625±17μm) and CF (p>0.05) and between CF and EIT (p>0.05). Compared to CF MEAs, SS MEAs had a lower discrimination power (103±51μm, p<0.05). COMPARISON WITH EXISTING METHODS: EIT and CF MEAs showed localisation power closest to MicroCT. Silicon MEAs adopted in this study failed to discriminate fascicle location. Re-design of probe geometry may improve results. CONCLUSIONS: Nerve EIT is an accurate tool for assessment of fascicular position within nerves. Accuracy of EIT and CF MEA is similar to the reference method. We give technical recommendations for performing multi-electrode recordings in nerves

Assessment of the use of space technology in the monitoring of oil spills and ocean pollution: Technical volume. Executive summary

The potential of space systems and technology for detecting and monitoring ocean oil spills and waste pollution was assessed as well as the impact of this application on communication and data handling systems. Agencies charged with responsibilities in this area were identified and their measurement requirements were ascertained in order to determine the spatial resolution needed to characterize operational and accidental discharges. Microwave and optical sensors and sensing techniques were evaluated as candidate system elements. Capabilities are described for the following: synthetic aperture radar, microwave scatterometer, passive microwave radiometer, microwave altimeter, electro-optical sensors currently used in airborne detection, existing space-based optical sensors, the thematic mapper, and the pointable optical linear array

Societal issues concerning the application of artificial intelligence in medicine

Medicine is becoming an increasingly data-centred discipline and, beyond classical statistical approaches, artificial intelligence (AI) and, in particular, machine learning (ML) are attracting much interest for the analysis of medical data. It has been argued that AI is experiencing a fast process of commodification. This characterization correctly reflects the current process of industrialization of AI and its reach into society. Therefore, societal issues related to the use of AI and ML should not be ignored any longer and certainly not in the medical domain. These societal issues may take many forms, but they all entail the design of models from a human-centred perspective, incorporating human-relevant requirements and constraints. In this brief paper, we discuss a number of specific issues affecting the use of AI and ML in medicine, such as fairness, privacy and anonymity, explainability and interpretability, but also some broader societal issues, such as ethics and legislation. We reckon that all of these are relevant aspects to consider in order to achieve the objective of fostering acceptance of AI- and ML-based technologies, as well as to comply with an evolving legislation concerning the impact of digital technologies on ethically and privacy sensitive matters. Our specific goal here is to reflect on how all these topics affect medical applications of AI and ML. This paper includes some of the contents of the “2nd Meeting of Science and Dialysis: Artificial Intelligence,” organized in the Bellvitge University Hospital, Barcelona, Spain.Peer ReviewedPostprint (author's final draft

Upper limb prostheses: bridging the sensory gap

Replacing human hand function with prostheses goes far beyond only recreating muscle movement with feedforward motor control. Natural sensory feedback is pivotal for fine dexterous control and finding both engineering and surgical solutions to replace this complex biological function is imperative to achieve prosthetic hand function that matches the human hand. This review outlines the nature of the problems underlying sensory restitution, the engineering methods that attempt to address this deficit and the surgical techniques that have been developed to integrate advanced neural interfaces with biological systems. Currently, there is no single solution to restore sensory feedback. Rather, encouraging animal models and early human studies have demonstrated that some elements of sensation can be restored to improve prosthetic control. However, these techniques are limited to highly specialized institutions and much further work is required to reproduce the results achieved, with the goal of increasing availability of advanced closed loop prostheses that allow sensory feedback to inform more precise feedforward control movements and increase functionality

A simulation study on the effects of neuronal ensemble properties on decoding algorithms for intracortical brain-machine interfaces

Background: Intracortical brain-machine interfaces (BMIs) harness movement information by sensing neuronal activities using chronic microelectrode implants to restore lost functions to patients with paralysis. However, neuronal signals often vary over time, even within a day, forcing one to rebuild a BMI every time they operate it. The term &quot;rebuild&quot; means overall procedures for operating a BMI, such as decoder selection, decoder training, and decoder testing. It gives rise to a practical issue of what decoder should be built for a given neuronal ensemble. This study aims to address it by exploring how decoders&apos; performance varies with the neuronal properties. To extensively explore a range of neuronal properties, we conduct a simulation study. Methods: Focusing on movement direction, we examine several basic neuronal properties, including the signal-to-noise ratio of neurons, the proportion of well-tuned neurons, the uniformity of their preferred directions (PDs), and the non-stationarity of PDs. We investigate the performance of three popular BMI decoders: Kalman filter, optimal linear estimator, and population vector algorithm. Results: Our simulation results showed that decoding performance of all the decoders was affected more by the proportion of well-tuned neurons that their uniformity. Conclusions: Our study suggests a simulated scenario of how to choose a decoder for intracortical BMIs in various neuronal conditions

Reach and grasp by people with tetraplegia using a neurally controlled robotic arm

Paralysis following spinal cord injury (SCI), brainstem stroke, amyotrophic lateral sclerosis (ALS) and other disorders can disconnect the brain from the body, eliminating the ability to carry out volitional movements. A neural interface system (NIS)1–5 could restore mobility and independence for people with paralysis by translating neuronal activity directly into control signals for assistive devices. We have previously shown that people with longstanding tetraplegia can use an NIS to move and click a computer cursor and to control physical devices6–8. Able-bodied monkeys have used an NIS to control a robotic arm9, but it is unknown whether people with profound upper extremity paralysis or limb loss could use cortical neuronal ensemble signals to direct useful arm actions. Here, we demonstrate the ability of two people with long-standing tetraplegia to use NIS-based control of a robotic arm to perform three-dimensional reach and grasp movements. Participants controlled the arm over a broad space without explicit training, using signals decoded from a small, local population of motor cortex (MI) neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the sensor five years earlier, also used a robotic arm to drink coffee from a bottle. While robotic reach and grasp actions were not as fast or accurate as those of an able-bodied person, our results demonstrate the feasibility for people with tetraplegia, years after CNS injury, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals