Neurotechnological cognitive enhancement has become an area of intense scientific, policy, and ethical interest. However, while work has increasingly focused on ethical views of the general public, less studied are those with personal connections to cognitive impairment. Using a mixed-methods design, we surveyed attitudes regarding implantable neurotechnological cognitive enhancement in individuals who self-identified as having increased likelihood of developing dementia (n = 25; 'Our Study'), compared to a nationally representative sample of Americans (n = 4726; 'Pew Study'). Participants in Our Study were additionally shown four videos showcasing hypothetical neurotechnological devices designed to enhance different cognitive abilities and were interviewed for more in-depth responses. Both groups expressed comparable degrees of worry and acknowledgement of potential ethical ramifications (all ps > 0.05). Compared to the Pew Study, participants in Our Study expressed slightly higher desire (p < 0.01), as well as higher acknowledgment for potential impacts on productivity (p < 0.05). Ultimately, participants in Our Study were more likely to deem the device morally acceptable (56%; compared to Pew Study, 25.2%; p = 0.0001). Interviews conducted in Our Study allowed participants to supply additional nuance and reasoning to survey responses, such as giving examples for increased productivity, perceived downsides of memory enhancement, or concerns regarding potentially resulting inequality. This study builds upon and adds to the growing focus on potential ethical issues surrounding neurotechnological cognitive enhancement by centering stakeholder perspectives, highlighting the need for inclusive research and consideration of diverse perspectives and lived experiences to ensure inclusive dialogue that best informs ethical and policy discussions in this rapidly advancing field.

Throughout its history, the field of brain-computer interfaces (BCIs) has offered people with severe motor disabilities the opportunity to engage with their environments using brain activity alone. Contemporary solutions, however, lack support for reliable evaluation by researchers, independent use by patients and their caregivers, or creative extension by students, artists, and software developers at home. This paper provides preliminary guidance on the integration of research engagement activities into BCI research to enable use at home. Alongside key principles for enabling Research Engagement Always And With Everyone, we present the initial specification for a standardized software ecosystem that could enable the rapid development of high-performance BCI applications on the Open Web. By integrating Open Web technologies alongside engagement activities in current research programs, we argue that participation in the development of a new generation of at-home BCI systems can be widened.

•Dementia at-risk population cautiously supports DBS research for cognition and behavior.•Thresholds for considering a future cognitive or behavioral treatment device vary.•Hypothetical cognitive and behavioral devices promise benefits and raise ethical concerns.

Background: Hippocampal memory prosthesis is defined as a closed-loop biomimetic system that can be used for restoration and enhancement of memory functions impaired in diseases or injuries. To build such a prosthesis, we have developed two types of input-output models, i.e., a multi-input multi-output (MIMO) model for predicting output spike trains based on input spikes, and a double-layer multi-resolution memory decoding (MD) model for classifying spatio-temporal patterns of spikes into memory categories. Both models can achieve high prediction accuracy using human hippocampal spikes data and can be used to derive electrical stimulation patterns to test the hippocampal memory prosthesis. Methods: However, testing hippocampal memory prostheses in human epilepsy patients with such models has to be performed within a much shorter time window (48-72 h) due to clinical limitations. To solve this problem, we have developed parallelization strategies to decompose the overall model estimation task into multiple independent sub-tasks involving different outputs and cross-validation folds. These sub-tasks are then accomplished in parallel on different computer nodes to reduce model estimation time. Results: Implementing both parallel schemes with a high-performance computer cluster, we successfully reduced the computing time of model estimations from hundreds of hours to tens of hours. Comparison with existing method: We have tested the two parallel computing schemes for both MIMO and MD models with data collected from 11 human subjects. The performances of the parallel schemes are compared with the performance of the non-parallel scheme. Conclusion: Such strategies allow us to complete the modeling procedure within the required time frame to further test input-output model-driven electrical stimulations for the hippocampal memory prosthesis. It has important implications to test the model-based DBS intraoperatively and developing clinically viable hippocampal memory prostheses.

During active tactile exploration, the dynamic patterns of touch are transduced to electrical signals and transformed by the brain into a mental representation of the object under investigation. This transformation from sensation to perception is thought to be a major function of the mammalian cortex. In primary somatosensory cortex (S1) of mice, layer 5 (L5) pyramidal neurons are major outputs to downstream areas that influence perception, decision-making, and motor control. We investigated self-motion and touch representations in L5 of S1 with juxtacellular loose-seal patch recordings of optogenetically identified excitatory neurons. We found that during rhythmic whisker movement, 54 of 115 active neurons (47%) represented self-motion. This population was significantly more modulated by whisker angle than by phase. Upon active touch, a distinct pattern of activity was evoked across L5, which represented the whisker angle at the time of touch. Object location was decodable with submillimeter precision from the touch-evoked spike counts of a randomly sampled handful of these neurons. These representations of whisker angle during self-motion and touch were independent, both in the selection of which neurons were active and in the angle-tuning preference of coactive neurons. Thus, the output of S1 transiently shifts from a representation of self-motion to an independent representation of explored object location during active touch.