ABSTRACT
OBJECTIVE: Brain areas implicated in semantic memory can be damaged in patients with epilepsy (PWE). However, it is challenging to delineate semantic processing deficits from acoustic, linguistic, and other verbal aspects in current neuropsychological assessments. We developed a new Visual-based Semantic Association Task (ViSAT) to evaluate nonverbal semantic processing in PWE. METHOD: The ViSAT was adapted from similar predecessors (Pyramids & Palm Trees test, PPT; Camels & Cactus Test, CCT) comprised of 100 unique trials using real-life color pictures that avoid demographic, cultural, and other potential confounds. We obtained performance data from 23 PWE participants and 24 control participants (Control), along with crowdsourced normative data from 54 Amazon Mechanical Turk (Mturk) workers. RESULTS: ViSAT reached a consensus >90% in 91.3% of trials compared to 83.6% in PPT and 82.9% in CCT. A deep learning model demonstrated that visual features of the stimulus images (color, shape; i.e., non-semantic) did not influence top answer choices (p = 0.577). The PWE group had lower accuracy than the Control group (p = 0.019). PWE had longer response times than the Control group in general and this was augmented for the semantic processing (trial answer) stage (both p < 0.001). CONCLUSIONS: This study demonstrated performance impairments in PWE that may reflect dysfunction of nonverbal semantic memory circuits, such as seizure onset zones overlapping with key semantic regions (e.g., anterior temporal lobe). The ViSAT paradigm avoids confounds, is repeatable/longitudinal, captures behavioral data, and is open-source, thus we propose it as a strong alternative for clinical and research assessment of nonverbal semantic memory.
ABSTRACT
The leading cause of disability of all ages worldwide is severe lower back pain. To address this untreated epidemic, further investigation is needed into the leading cause of back pain, intervertebral disc degeneration. In particular, microphysiological systems modeling critical tissues in a degenerative disc, like the annulus fibrosus (AF), are needed to investigate the effects of complex multiaxial strains on AF cells. By replicating these mechanobiological effects unique to the AF that are not yet understood, we can advance therapies for early-stage degeneration at the cellular level. To this end, we designed, fabricated, and collected proof-of-concept data for a novel microphysiological device called the flexing annulus-on-a-chip (AoC). We used computational models and experimental measurements to characterize the device's ability to mimic complex physiologically relevant strains. As a result, these strains proved to be controllable, multi-directional, and uniformly distributed with magnitudes ranging from - 10 % to 12% in the axial, radial, and circumferential directions, which differ greatly from applied strains possible in uniaxial devices. Furthermore, after withstanding accelerated life testing (66 K cycles of 10% strain) and maintaining 2000 bovine AF cells without loading for more than three weeks the AoC proved capable of long-term cell culture. Additionally, after strain (3.5% strain for 75 cycles at 0.5 Hz) was applied to a monolayer of AF cells in the AoC, a population remained adhered to the channel with spread morphology. The AoC can also be tailored for other annular structures in the body such as cardiovascular vessels, lymphatic vessels, and the cervix.