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Brande-Eilat, N.

Publications and source records attributed to Brande-Eilat, N..

3 recordsLinked to original sources

BRAIN-BASED AUTHENTICATION: TOWARDS A SCALABLE, COMMERCIAL GRADE SOLUTION USING NONINVASIVE BRAIN SIGNALS.

Here we report on a field test where we asked if it is feasible to deliver a scalable, commercial-grade solution for brain-based authentication given currently available head wearables. In this study, forty-nine (49) participants completed multiple sessions in their natural home environment over a single week. Participants used an off-the-shelf brain signal measuring headband to record their own brain activity while completing various tasks. Recording sessions were self-operated by the participants and unsupervised by any expert or technician to simulate real world use cases, while also contrasting common research approaches to this topic that rely on data from controlled laboratory conditions. Although brain signals have a non-stationary, complex nature, when participants watched rapidly presented images, our authentication system was able to successfully construct a unique and robust "brain ID" for each participant. Based on this brain ID, we developed a simplified brain-based authentication method that captures distinguishable information with reliable, commercial-grade performance from participants at their own homes. We conclude that noninvasively measured brain signals are ideal for use in biometric authentication systems, especially in environments where head wearables such as headphones or AR/VR devices are used as these devices offer a natural form factor for capturing participant brain ID continuously.

neuroscience↗

DIFFERENCES IN THE EFFECTS ON HUMAN FOCUS OF MUSIC PLAYLISTS AND PERSONALIZED SOUNDSCAPES, AS MEASURED BY BRAIN SIGNALS.

The goal of this study was to investigate the effect of sounds on human focus and to identify the properties that contribute most to increasing and decreasing focus in people within their natural, everyday environment. Participants (N=62, 18-65y) performed various tasks on a tablet computer while listening to either no background sounds (silence), popular music playlists designed to increase focus (pre-recorded songs in a particular sequence), or engineered soundscapes that were personalized to individual listeners (digital audio composed in real-time based on input parameters such as heart rate, time of day, location, etc.). Sounds were delivered to participants through headphones while simultaneously their brain signals were recorded by a portable electroencephalography headband. Participants completed four one-hour long sessions at home during which different sound content played continuously. Using brain decoding technology, we obtained individual participant focus levels over time and used this data to analyze the effects of various properties of sound. We found that while participants were working, personalized soundscapes increased their focus significantly above silence (p=0.008), while music playlists did not have a significant effect. For the young adult demographic (18-36y), all sound content tested was significantly better than silence at producing focus (p=0.001-0.009). Personalized soundscapes increased focus the most relative to silence, but playlists of pre-recorded songs also increased focus significantly during specific time intervals. Ultimately we found that it is possible to accurately predict human focus levels that will be experienced in response to sounds a priori based on the sounds physical properties. We then applied this finding to compare between music genres and revealed that classical music, engineered soundscapes, and natural sounds were the best genres for increasing focus, while pop and hip-hop were the worst. These insights can enable human and artificial intelligence composers to produce increases or decreases in listener focus with high temporal (millisecond) precision. Future research will include real-time adaptation of sound libraries for other functional objectives beyond affecting focus, such as affecting listener enjoyment, stress, and memory.

neuroscience↗

Revealing neural correlates of behavior without behavioral measurements

Measuring neuronal tuning curves has been instrumental for many discoveries in neuroscience but requires a-priori assumptions regarding the identity of the encoded variables. We applied unsupervised learning to large-scale neuronal recordings in behaving mice from circuits involved in spatial cognition, and uncovered a highly-organized internal structure of ensemble activity patterns. This emergent structure allowed defining for each neuron an internal tuning-curve that characterizes its activity relative to the network activity, rather than relative to any pre-defined external variable - revealing place-tuning in the hippocampus and head-direction tuning in the thalamus and postsubiculum, without relying on measurements of place or head-direction. Similar investigation in prefrontal cortex revealed schematic representations of distances and actions, and exposed a previously unknown variable, the trajectory-phase. The structure of ensemble activity patterns was conserved across mice, allowing using one animals data to decode another animals behavior. Thus, the internal structure of neuronal activity itself enables reconstructing internal representations and discovering new behavioral variables hidden within a neural code.

neuroscience↗