Person:
Widge, Alik

Profile Picture

Email Address

AA Acceptance Date

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

Widge

First Name

Alik

Name

Widge, Alik
Author's Publications: search.filters.isAuthorOfPublication.d9e785de-3549-4a59-8ebd-a865012219e2

Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    Publication
    Closing the Loop on Deep Brain Stimulation for Treatment-Resistant Depression
    (Frontiers Media S.A., 2018) Widge, Alik; Malone, Donald A.; Dougherty, Darin
    Major depressive episodes are the largest cause of psychiatric disability, and can often resist treatment with medication and psychotherapy. Advances in the understanding of the neural circuit basis of depression, combined with the success of deep brain stimulation (DBS) in movement disorders, spurred several groups to test DBS for treatment-resistant depression. Multiple brain sites have now been stimulated in open-label and blinded studies. Initial open-label results were dramatic, but follow-on controlled/blinded clinical trials produced inconsistent results, with both successes and failures to meet endpoints. Data from follow-on studies suggest that this is because DBS in these trials was not targeted to achieve physiologic responses. We review these results within a technology-lifecycle framework, in which these early trial “failures” are a natural consequence of over-enthusiasm for an immature technology. That framework predicts that from this “valley of disillusionment,” DBS may be nearing a “slope of enlightenment.” Specifically, by combining recent mechanistic insights and the maturing technology of brain-computer interfaces (BCI), the next generation of trials will be better able to target pathophysiology. Key to that will be the development of closed-loop systems that semi-autonomously alter stimulation strategies based on a patient's individual phenotype. Such next-generation DBS approaches hold great promise for improving psychiatric care.
  • Thumbnail Image
    Publication
    Avoiding a lost generation of scientists
    (eLife Sciences Publications, Ltd, 2016) Taylor, Justin Q; Kovacik, Peter; Traer, James; Zakahi, Philip; Oslowski, Christine; Widge, Alik; Glorioso, Christin A
    By sharing their experiences, early-career scientists can help to make the case for increased government funding for researchers.
  • Thumbnail Image
    Publication
    Estimating Dynamic Signals From Trial Data With Censored Values
    (MIT Press, 2017) Yousefi, Ali; Dougherty, Darin; Eskandar, Emad; Widge, Alik; Eden, Uri T.
    Censored data occur commonly in trial-structured behavioral experiments and many other forms of longitudinal data. They can lead to severe bias and reduction of statistical power in subsequent analyses. Principled approaches for dealing with censored data, such as data imputation and methods based on the complete data’s likelihood, work well for estimating fixed features of statistical models but have not been extended to dynamic measures, such as serial estimates of an underlying latent variable over time. Here we propose an approach to the censored-data problem for dynamic behavioral signals. We developed a state-space modeling framework with a censored observation process at the trial timescale. We then developed a filter algorithm to compute the posterior distribution of the state process using the available data. We showed that special cases of this framework can incorporate the three most common approaches to censored observations: ignoring trials with censored data, imputing the censored data values, or using the full information available in the data likelihood. Finally, we derived a computationally efficient approximate Gaussian filter that is similar in structure to a Kalman filter, but that efficiently accounts for censored data. We compared the performances of these methods in a simulation study and provide recommendations of approaches to use, based on the expected amount of censored data in an experiment. These new techniques can broadly be applied in many research domains in which censored data interfere with estimation, including survival analysis and other clinical trial applications.
  • Thumbnail Image
    Publication
    A Sub-millimeter, Inductively Powered Neural Stimulator
    (Frontiers Media S.A., 2017) Freeman, Daniel K.; O'Brien, Jonathan M.; Kumar, Parshant; Daniels, Brian; Irion, Reed A.; Shraytah, Louis; Ingersoll, Brett K.; Magyar, Andrew P.; Czarnecki, Andrew; Wheeler, Jesse; Coppeta, Jonathan R.; Abban, Michael P.; Gatzke, Ronald; Fried, Shelley; Lee, Seung Woo; Duwel, Amy E.; Bernstein, Jonathan J.; Widge, Alik; Hernandez-Reynoso, Ana; Kanneganti, Aswini; Romero-Ortega, Mario I.; Cogan, Stuart F.
    Wireless neural stimulators are being developed to address problems associated with traditional lead-based implants. However, designing wireless stimulators on the sub-millimeter scale (<1 mm3) is challenging. As device size shrinks, it becomes difficult to deliver sufficient wireless power to operate the device. Here, we present a sub-millimeter, inductively powered neural stimulator consisting only of a coil to receive power, a capacitor to tune the resonant frequency of the receiver, and a diode to rectify the radio-frequency signal to produce neural excitation. By replacing any complex receiver circuitry with a simple rectifier, we have reduced the required voltage levels that are needed to operate the device from 0.5 to 1 V (e.g., for CMOS) to ~0.25–0.5 V. This reduced voltage allows the use of smaller receive antennas for power, resulting in a device volume of 0.3–0.5 mm3. The device was encapsulated in epoxy, and successfully passed accelerated lifetime tests in 80°C saline for 2 weeks. We demonstrate a basic proof-of-concept using stimulation with tens of microamps of current delivered to the sciatic nerve in rat to produce a motor response.