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    Strategic stabilization of arousal boosts sustained attention
    (Elsevier, 2024) de Gee, Jan Willem; Mridha, Zakir; Hudson, Marisa; Shi, Yanchen; Ramsaywak, Hannah; Smith, Spencer; Karediya, Nishad; Thompson, Matthew; Jaspe, Kit; Jiang, Hong; Zhang, Wenhao; McGinley, Matthew J.
    Arousal and motivation interact to profoundly influence behavior. For example, experience tells us that we have some capacity to control our arousal when appropriately motivated, such as staying awake while driving a motor vehicle. However, little is known about how arousal and motivation jointly influence decision computations, including if and how animals, such as rodents, adapt their arousal state to their needs. Here, we developed and show results from an auditory, feature-based, sustained-attention task with intermittently shifting task utility. We use pupil size to estimate arousal across a wide range of states and apply tailored signal-detection theoretic, hazard function, and accumulation-to-bound modeling approaches in a large cohort of mice. We find that pupil-linked arousal and task utility both have major impacts on multiple aspects of task performance. Although substantial arousal fluctuations persist across utility conditions, mice partially stabilize their arousal near an intermediate and optimal level when task utility is high. Behavioral analyses show that multiple elements of behavior improve during high task utility and that arousal influences some, but not all, of them. Specifically, arousal influences the likelihood and timescale of sensory evidence accumulation but not the quantity of evidence accumulated per time step while attending. In sum, the results establish specific decision-computational signatures of arousal, motivation, and their interaction in attention. So doing, we provide an experimental and analysis framework for studying arousal self-regulation in neurotypical brains and in diseases such as attention-deficit/hyperactivity disorder.
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    Towards objective, temporally resolved neurobehavioral predictors of emotional state
    (Elsevier, 2024) Kabotyanski, Katherine E.; Yi, Han G.; Hingorani, Rahul; Robinson, Brian S.; Cowley, Hannah P.; Fifer, Matthew S.; Wester, Brock A.; Lamichhane, Bishal; Sabharwal, Ashutosh; Allawala, Anusha B.; Rajesh, Sameer V.; Diab, Nabeel; Mathura, Raissa K.; Pirtle, Victoria; Adkinson, Joshua; Watrous, Andrew J.; Bartoli, Eleonora; Xiao, Jiayang; Banks, Garrett P.; Mathew, Sanjay J.; Goodman, Wayne K.; Pitkow, Xaq; Pouratian, Nader; Hayden, Benjamin Y.; Provenza, Nicole R.; Sheth, Sameer A.
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    Technology and health inequities in diabetes care: How do we widen access to underserved populations and utilize technology to improve outcomes for all?
    (Wiley, 2024) Ebekozien, Osagie; Fantasia, Kathryn; Farrokhi, Farnoosh; Sabharwal, Ashutosh; Kerr, David
    Abstract Digital health technologies are being utilized increasingly in the modern management of diabetes. These include tools such as continuous glucose monitoring systems, connected blood glucose monitoring devices, hybrid closed-loop systems, smart insulin pens, telehealth, and smartphone applications (apps). Although many of these technologies have a solid evidence base, from the perspective of a person living with diabetes, there remain multiple barriers preventing their optimal use, creating a digital divide. In this article, we describe many of the origins of these barriers and offer recommendations on widening access to digital health technologies for underserved populations living with diabetes to improve their health outcomes.
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    Phototaxis is a satiety-dependent behavioral sequence in Hydra vulgaris
    (The Company of Biologists, 2024) Kim, Soonyoung; Badhiwala, Krishna N.; Duret, Guillaume; Robinson, Jacob T.
    Understanding how internal states such as satiety are connected to animal behavior is a fundamental question in neuroscience. Hydra vulgaris, a freshwater cnidarian with only 12 neuronal cell types, serves as a tractable model system for studying state-dependent behaviors. We found that starved hydras consistently move towards light, while fed hydras do not. By modeling this behavior as a set of three sequences of head orientation, jump distance and jump rate, we demonstrate that the satiety state only affects the rate of the animal jumping to a new position, while the orientation and jump distance are unaffected. These findings yield insights into how internal states in a simple organism, Hydra, affect specific elements of a behavior, and offer general principles for studying the relationship between state-dependent behaviors and their underlying molecular mechanisms.
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    A frequency-agile retrodirective tag for large-scale sub-terahertz data backscattering
    (Springer Nature, 2024) Kludze, Atsutse; Kono, Junichiro; Mittleman, Daniel M.; Ghasempour, Yasaman
    Backscattering is a promising power-efficient communication technique providing sustainable wireless links with a low carbon footprint. This approach is a critical enabler for dense IoT networks, which are forecast to grow to 41 billion by 2025. However, existing backscatter designs are limited to the sub-6 GHz bands or narrowband operation in the millimeter-wave regime; therefore, they fail to concurrently support many interference-free low-power users. Enabling a frequency-agile wideband backscatter design in the sub-terahertz offers a two-pronged advantage for densely deployed backscatter networks: spatial reuse enabled by directionality and frequency multiplexing enabled by the large available bandwidth. We present the first sub-THz backscatter architecture that operates above 100 GHz. Our design relies on a detailed understanding of reciprocity in leaky-wave devices and offers a realistic joint localization and communication protocol for sub-THz backscatter networks.
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    Magnetoelectrics for Implantable Bioelectronics: Progress to Date
    (American Chemical Society, 2024) Alrashdan, Fatima; Yang, Kaiyuan; Robinson, Jacob T.; Applied Physics Program
    ConspectusThe coupling of magnetic and electric properties manifested in magnetoelectric (ME) materials has unlocked numerous possibilities for advancing technologies like energy harvesting, memory devices, and medical technologies. Due to this unique coupling, the magnetic properties of these materials can be tuned by an electric field; conversely, their electric polarization can be manipulated through a magnetic field.Over the past seven years, our lab work has focused on leveraging these materials to engineer implantable bioelectronics for various neuromodulation applications. One of the main challenges for bioelectronics is to design miniaturized solutions that can be delivered with minimally invasive procedures and yet can receive sufficient power to directly stimulate tissue or power electronics to perform functions like communication and sensing.Magnetoelectric coupling in ME materials is strongest when the driving field matches a mechanical resonant mode. However, miniaturized ME transducers typically have resonance frequencies >100 kHz, which is too high for direct neuromodulation as neurons only respond to low frequencies (typically <1 kHz). We discuss two approaches that have been proposed to overcome this frequency mismatch: operating off-resonance and rectification. The off-resonance approach is most common for magnetoelectric nanoparticles (MENPs) that typically have resonance frequencies in the gigahertz range. In vivo experiments on rat models have shown that MENPs could induce changes in neural activity upon excitation with <200 Hz magnetic fields. However, the neural response has latencies of several seconds due to the weak coupling in the off-resonance regime.To stimulate neural responses with millisecond precision, we developed methods to rectify the ME response so that we could drive the materials at their resonant frequency but still produce the slowly varying voltages needed for direct neural stimulation. The first version of the stimulator combined a ME transducer and analog electronics for rectification. To create even smaller solutions, we introduced the first magnetoelectric metamaterial (MNM) that exhibits self-rectification. Both designs have effectively induced neural modulation in rat models with less than 5 ms latency.Based on our experience with in vivo testing of the rectified ME stimulators, we found it challenging to deliver the precisely controlled therapy required for clinical applications, given the ME transducer’s sensitivity to the external transmitter alignment. To overcome this challenge, we developed the ME-BIT (MagnetoElectric BioImplanT), a digitally programmable stimulator that receives wireless power and data through the ME link.We further expanded the utility of this technology to neuromodulation applications that require high stimulation thresholds by introducing the DOT (Digitally programmable Overbrain Therapeutic). The DOT has voltage compliance up to 14.5 V. We have demonstrated the efficacy of these designs through various in vivo studies for applications like peripheral nerve stimulation and epidural cortical stimulation.To further improve these systems to be adaptive and enable a network of coordinated devices, we developed a bidirectional communication system to transmit data to and from the implant. To enable even greater miniaturization, we developed a way to use the same ME transducer for wireless power and data communication by developing the first ME backscatter communication protocol.
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    Evaluating HbA1c-to-average glucose conversion with patient-specific kinetic models for diverse populations
    (Springer Nature, 2024) Sato Imuro, Sandra Emi; Sabharwal, Ashutosh; Bevier, Wendy; Kerr, David
    The discrepancy between estimated glycemia from HbA1c values and actual average glucose (AG) levels has significant implications for treatment decisions and patient understanding. Factors contributing to the gap include red blood cell (RBC) lifespan and glucose uptake into the RBC. Personalized models have been proposed to enhance AG prediction accuracy by considering interpersonal variation. This study contributes to our understanding of personalized models for estimating AG from HbA1c. Utilizing data from seven studies (340 participants), including Hispanic/Latino populations with or at risk of non-insulin-treated type 2 diabetes (T2D), we examined kinetic features across cohorts. Additionally, the study simulated scenarios to understand data requirements for improving accuracy. Personalized approaches improved agreement between AG estimations and CGM-AG, particularly with four or more weeks of training CGM data. A multiple linear regression model using kinetic parameters and added clinical features was shown to improve the accuracy of personalized models further. As CGM usage extends beyond type 1 diabetes, there is growing interest in leveraging CGM data for clinical decision-making. Patient-specific models offer a valuable tool for managing glycemic status in patients with discordant HbA1c and AG values.
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    Reversible non-volatile electronic switching in a near-room-temperature van der Waals ferromagnet
    (Springer Nature, 2024) Wu, Han; Chen, Lei; Malinowski, Paul; Jang, Bo Gyu; Deng, Qinwen; Scott, Kirsty; Huang, Jianwei; Ruff, Jacob P. C.; He, Yu; Chen, Xiang; Hu, Chaowei; Yue, Ziqin; Oh, Ji Seop; Teng, Xiaokun; Guo, Yucheng; Klemm, Mason; Shi, Chuqiao; Shi, Yue; Setty, Chandan; Werner, Tyler; Hashimoto, Makoto; Lu, Donghui; Yilmaz, Turgut; Vescovo, Elio; Mo, Sung-Kwan; Fedorov, Alexei; Denlinger, Jonathan D.; Xie, Yaofeng; Gao, Bin; Kono, Junichiro; Dai, Pengcheng; Han, Yimo; Xu, Xiaodong; Birgeneau, Robert J.; Zhu, Jian-Xin; da Silva Neto, Eduardo H.; Wu, Liang; Chu, Jiun-Haw; Si, Qimiao; Yi, Ming; Rice Center for Quantum Materials
    Non-volatile phase-change memory devices utilize local heating to toggle between crystalline and amorphous states with distinct electrical properties. Expanding on this kind of switching to two topologically distinct phases requires controlled non-volatile switching between two crystalline phases with distinct symmetries. Here, we report the observation of reversible and non-volatile switching between two stable and closely related crystal structures, with remarkably distinct electronic structures, in the near-room-temperature van der Waals ferromagnet Fe5−δGeTe2. We show that the switching is enabled by the ordering and disordering of Fe site vacancies that results in distinct crystalline symmetries of the two phases, which can be controlled by a thermal annealing and quenching method. The two phases are distinguished by the presence of topological nodal lines due to the preserved global inversion symmetry in the site-disordered phase, flat bands resulting from quantum destructive interference on a bipartite lattice, and broken inversion symmetry in the site-ordered phase.
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    Sharp-peaked lanthanide nanocrystals for near-infrared photoacoustic multiplexed differential imaging
    (Springer Nature, 2024) Loh, Kang Yong; Li, Lei S.; Fan, Jingyue; Goh, Yi Yiing; Liew, Weng Heng; Davis, Samuel; Zhang, Yide; Li, Kai; Liu, Jie; Liang, Liangliang; Feng, Minjun; Yang, Ming; Zhang, Hang; Ma, Ping’an; Feng, Guangxue; Mu, Zhao; Gao, Weibo; Sum, Tze Chien; Liu, Bin; Lin, Jun; Yao, Kui; Wang, Lihong V.; Liu, Xiaogang
    Photoacoustic tomography offers a powerful tool to visualize biologically relevant molecules and understand processes within living systems at high resolution in deep tissue, facilitated by the conversion of incident photons into low-scattering acoustic waves through non-radiative relaxation. Although current endogenous and exogenous photoacoustic contrast agents effectively enable molecular imaging within deep tissues, their broad absorption spectra in the visible to near-infrared (NIR) range limit photoacoustic multiplexed imaging. Here, we exploit the distinct ultrasharp NIR absorption peaks of lanthanides to engineer a series of NIR photoacoustic nanocrystals. This engineering involves precise host and dopant material composition, yielding nanocrystals with sharply peaked photoacoustic absorption spectra (~3.2 nm width) and a ~10-fold enhancement in NIR optical absorption for efficient deep tissue imaging. By combining photoacoustic tomography with these engineered nanocrystals, we demonstrate photoacoustic multiplexed differential imaging with substantially decreased background signals and enhanced precision and contrast.
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    Strong nonlinear optical processes with extraordinary polarization anisotropy in inversion-symmetry broken two-dimensional PdPSe
    (Springer Nature, 2024) Zhu, Song; Duan, Ruihuan; Xu, Xiaodong; Sun, Fangyuan; Chen, Wenduo; Wang, Fakun; Li, Siyuan; Ye, Ming; Zhou, Xin; Cheng, Jinluo; Wu, Yao; Liang, Houkun; Kono, Junichiro; Li, Xingji; Liu, Zheng; Wang, Qi Jie
    Nonlinear optical activities, especially second harmonic generation (SHG), are key phenomena in inversion-symmetry-broken two-dimensional (2D) transition metal dichalcogenides (TMDCs). On the other hand, anisotropic nonlinear optical processes are important for unique applications in nano-nonlinear photonic devices with polarization functions, having become one of focused research topics in the field of nonlinear photonics. However, the strong nonlinearity and strong optical anisotropy do not exist simultaneously in common 2D materials. Here, we demonstrate strong second-order and third-order susceptibilities of 64 pm/V and 6.2×10−19 m2/V2, respectively, in the even-layer PdPSe, which has not been discovered in other common TMDCs (e.g., MoS2). Strikingly, it also simultaneously exhibited strong SHG anisotropy with an anisotropic ratio of ~45, which is the largest reported among all 2D materials to date, to the best of our knowledge. In addition, the SHG anisotropy ratio can be harnessed from 0.12 to 45 (375 times) by varying the excitation wavelength due to the dispersion of $${\chi }^{(2)}$$values. As an illustrative example, we further demonstrate polarized SHG imaging for potential applications in crystal orientation identification and polarization-dependent spatial encoding. These findings in 2D PdPSe are promising for nonlinear nanophotonic and optoelectronic applications.
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    Audio misinformation encoding via an on-phone sub-terahertz metasurface
    (Optica Publishing Group, 2024) Shaikhanov, Zhambyl; Al-Madi, Mahmoud; Chen, Hou-Tong; Chang, Chun-Chieh; Addamane, Sadhvikas; Mittleman, Daniel M.; Knightly, Edward W.
    We demonstrate a wireless security application to protect the weakest link in phone-to-phone communication, using a terahertz metasurface. To our knowledge, this is the first example of an eavesdropping countermeasure in which the attacker is actively misled.
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    Quantum simulation of an extended Dicke model with a magnetic solid
    (Springer Nature, 2024) Marquez Peraca, Nicolas; Li, Xinwei; Moya, Jaime M.; Hayashida, Kenji; Kim, Dasom; Ma, Xiaoxuan; Neubauer, Kelly J.; Fallas Padilla, Diego; Huang, Chien-Lung; Dai, Pengcheng; Nevidomskyy, Andriy H.; Pu, Han; Morosan, Emilia; Cao, Shixun; Bamba, Motoaki; Kono, Junichiro
    The Dicke model describes the cooperative interaction of an ensemble of two-level atoms with a single-mode photonic field and exhibits a quantum phase transition as a function of light–matter coupling strength. Extending this model by incorporating short-range atom–atom interactions makes the problem intractable but is expected to produce new physical phenomena and phases. Here, we simulate such an extended Dicke model using a crystal of ErFeO3, where the role of atoms (photons) is played by Er3+ spins (Fe3+ magnons). Through terahertz spectroscopy and magnetocaloric effect measurements as a function of temperature and magnetic field, we demonstrated the existence of a novel atomically ordered phase in addition to the superradiant and normal phases that are expected from the standard Dicke model. Further, we elucidated the nature of the phase boundaries in the temperature–magnetic-field phase diagram, identifying both first-order and second-order phase transitions. These results lay the foundation for studying multiatomic quantum optics models using well-characterized many-body solid-state systems.
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    Reference-free structural variant detection in microbiomes via long-read co-assembly graphs
    (Oxford University Press, 2024) Curry, Kristen D; Yu, Feiqiao Brian; Vance, Summer E; Segarra, Santiago; Bhaya, Devaki; Chikhi, Rayan; Rocha, Eduardo P C; Treangen, Todd J
    Motivation: The study of bacterial genome dynamics is vital for understanding the mechanisms underlying microbial adaptation, growth, and their impact on host phenotype. Structural variants (SVs), genomic alterations of 50 base pairs or more, play a pivotal role in driving evolutionary processes and maintaining genomic heterogeneity within bacterial populations. While SV detection in isolate genomes is relatively straightforward, metagenomes present broader challenges due to the absence of clear reference genomes and the presence of mixed strains. In response, our proposed method rhea, forgoes reference genomes and metagenome-assembled genomes (MAGs) by encompassing all metagenomic samples in a series (time or other metric) into a single co-assembly graph. The log fold change in graph coverage between successive samples is then calculated to call SVs that are thriving or declining.Results: We show rhea to outperform existing methods for SV and horizontal gene transfer (HGT) detection in two simulated mock metagenomes, particularly as the simulated reads diverge from reference genomes and an increase in strain diversity is incorporated. We additionally demonstrate use cases for rhea on series metagenomic data of environmental and fermented food microbiomes to detect specific sequence alterations between successive time and temperature samples, suggesting host advantage. Our approach leverages previous work in assembly graph structural and coverage patterns to provide versatility in studying SVs across diverse and poorly characterized microbial communities for more comprehensive insights into microbial gene flux.Availability and implementation: rhea is open source and available at: https://github.com/treangenlab/rhea.
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    Mobile sensing-based depression severity assessment in participants with heterogeneous mental health conditions
    (Springer Nature, 2024) Lamichhane, Bishal; Moukaddam, Nidal; Sabharwal, Ashutosh
    Mobile sensing-based depression severity assessment could complement the subjective questionnaires-based assessment currently used in practice. However, previous studies on mobile sensing for depression severity assessment were conducted on homogeneous mental health condition participants; evaluation of possible generalization across heterogeneous groups has been limited. Similarly, previous studies have not investigated the potential of free-living audio data for depression severity assessment. Audio recordings from free-living could provide rich sociability features to characterize depressive states. We conducted a study with 11 healthy individuals, 13 individuals with major depressive disorder, and eight individuals with schizoaffective disorders. Communication logs and location data from the participants’ smartphones and continuous audio recordings of free-living from a wearable audioband were obtained over a week for each participant. The depression severity prediction model trained using communication log and location data features had a root mean squared error (rmse) of 6.80. Audio-based sociability features further reduced the rmse to 6.07 (normalized rmse of 0.22). Audio-based sociability features also improved the F1 score in the five-class depression category classification model from 0.34 to 0.46. Thus, free-living audio-based sociability features complement the commonly used mobile sensing features to improve depression severity assessment. The prediction results obtained with mobile sensing-based features are better than the rmse of 9.83 (normalized rmse of 0.36) and the F1 score of 0.25 obtained with a baseline model. Additionally, the predicted depression severity had a significant correlation with reported depression severity (correlation coefficient of 0.76, $$p<$$0.001). Thus, our work shows that mobile sensing could model depression severity across participants with heterogeneous mental health conditions, potentially offering a screening tool for depressive symptoms monitoring in the broader population.
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    A Detailed Clinical Case of Localized Prostate Tumors Treated with Nanoparticle-Assisted Sub-Ablative Laser Ablation
    (MDPI, 2024) Kadria-Vili, Yara; Schwartz, Jon A.; Polascik, Thomas J.; Goodrich, Glenn P.; Jorden, David; Pinder, Diane; Halas, Naomi J.; Rastinehad, Ardeshir R.; Laboratory for Nanophotonics
    AuroLase® Therapy—a nanoparticle-enabled focal therapy—has the potential to safely and effectively treat localized prostate cancer (PCa), preserving baseline functionality. This article presents a detailed case of localized PCa treated with AuroLase, providing insight on expectations from the diagnosis of PCa to one year post-treatment. AuroLase Therapy is a two-day treatment consisting of a systemic infusion of gold nanoshells (~150-nm hydrodynamic diameter) on Day 1, and sub-ablative laser treatment on Day 2. Multiparametric MRI (mpMRI) was used for tumor visualization, treatment planning, and therapy response assessment. The PCa was targeted with a MR/Ultrasound-fusion (MR/US) transperineal approach. Successful treatment was confirmed at 6 and 12 months post-treatment by the absence of disease in MR/US targeted biopsies. On the mpMRI, confined void space was evident, an indication of necrotic tissues encompassing the treated lesion, which was completely resolved at 12 months, forming a band-like scar with no evidence of recurrent tumor. The patient’s urinary and sexual functions were unchanged. During the one-year follow-up, changes on the DCE sequence and in the Ktrans and ADC values assist in qualitatively and quantitatively evaluating tissue changes. The results highlight the potential of gold-nanoparticle-enabled sub-ablative laser treatment to target and control localized PCa, maintain quality of life, and preserve baseline functionality.
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    Adaptation of sleep to daylight saving time is slower in people consuming a high-fat diet
    (Elsevier, 2024) McHill, Andrew W.; Sano, Akane; Barger, Laura K.; Phillips, Andrew J. K.; Czeisler, Charles A.; Klerman, Elizabeth B.
    Adaptation of the circadian clock to the environment is essential for optimal health, well-being, and performance. Animal models demonstrate that a high-fat diet impairs circadian adaptation to advances of the light-dark cycle; it is unknown whether this occurs in humans. Utilizing a natural experiment that occurs when humans must advance their behaviors to an earlier hour for daylight saving time (DST), we measured the influence of diet on sleep/wake timing relative to dim-light melatonin onset time. Students with a lower-fat diet rapidly altered their sleep-wake timing to match the imposed time change, whereas those with a high-fat diet were slower to adapt to the time change. Moreover, a faster shift in timing after DST was associated with higher general health, lower body mass index, and higher grade point average. These data suggest that diet may influence the speed of sleep and circadian adaptation, which could have implications for health and performance.
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    Multimodal illumination platform for 3D single-molecule super-resolution imaging throughout mammalian cells
    (Optica Publishing Group, 2024) Nelson, Tyler; Vargas-Hernández, Sofía; Freire, Margareth; Cheng, Siyang; Gustavsson, Anna-Karin; Smalley-Curl Institute;Institute of Biosciences & Bioengineering;Center for Nanoscale Imaging Sciences
    Single-molecule super-resolution imaging is instrumental in investigating cellular architecture and organization at the nanoscale. Achieving precise 3D nanometric localization when imaging structures throughout mammalian cells, which can be multiple microns thick, requires careful selection of the illumination scheme in order to optimize the fluorescence signal to background ratio (SBR). Thus, an optical platform that combines different wide-field illumination schemes for target-specific SBR optimization would facilitate more precise 3D nanoscale studies of a wide range of cellular structures. Here, we demonstrate a versatile multimodal illumination platform that integrates the sectioning and background reduction capabilities of light sheet illumination with homogeneous, flat-field epi- and TIRF illumination. Using primarily commercially available parts, we combine the fast and convenient switching between illumination modalities with point spread function engineering to enable 3D single-molecule super-resolution imaging throughout mammalian cells. For targets directly at the coverslip, the homogenous intensity profile and excellent sectioning of our flat-field TIRF illumination scheme improves single-molecule data quality by providing low fluorescence background and uniform fluorophore blinking kinetics, fluorescence signal, and localization precision across the entire field of view. The increased contrast achieved with LS illumination, when compared with epi-illumination, makes this illumination modality an excellent alternative when imaging targets that extend throughout the cell. We validate our microscopy platform for improved 3D super-resolution imaging by two-color imaging of paxillin – a protein located in the focal adhesion complex – and actin in human osteosarcoma cells.
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    Molecular scale nanophotonics: hot carriers, strong coupling, and electrically driven plasmonic processes
    (De Gruyter, 2024) Zhu, Yunxuan; Raschke, Markus B.; Natelson, Douglas; Cui, Longji
    Plasmonic modes confined to metallic nanostructures at the atomic and molecular scale push the boundaries of light–matter interactions. Within these extreme plasmonic structures of ultrathin nanogaps, coupled nanoparticles, and tunnelling junctions, new physical phenomena arise when plasmon resonances couple to electronic, exitonic, or vibrational excitations, as well as the efficient generation of non-radiative hot carriers. This review surveys the latest experimental and theoretical advances in the regime of extreme nano-plasmonics, with an emphasis on plasmon-induced hot carriers, strong coupling effects, and electrically driven processes at the molecular scale. We will also highlight related nanophotonic and optoelectronic applications including plasmon-enhanced molecular light sources, photocatalysis, photodetection, and strong coupling with low dimensional materials.
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    Inductive biases of neural network modularity in spatial navigation
    (AAAS, 2024) Zhang, Ruiyi; Pitkow, Xaq; Angelaki, Dora E.
    The brain may have evolved a modular architecture for daily tasks, with circuits featuring functionally specialized modules that match the task structure. We hypothesize that this architecture enables better learning and generalization than architectures with less specialized modules. To test this, we trained reinforcement learning agents with various neural architectures on a naturalistic navigation task. We found that the modular agent, with an architecture that segregates computations of state representation, value, and action into specialized modules, achieved better learning and generalization. Its learned state representation combines prediction and observation, weighted by their relative uncertainty, akin to recursive Bayesian estimation. This agent’s behavior also resembles macaques’ behavior more closely. Our results shed light on the possible rationale for the brain’s modularity and suggest that artificial systems can use this insight from neuroscience to improve learning and generalization in natural tasks.
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    Learning to express reward prediction error-like dopaminergic activity requires plastic representations of time
    (Springer Nature, 2024) Cone, Ian; Clopath, Claudia; Shouval, Harel Z.
    The dominant theoretical framework to account for reinforcement learning in the brain is temporal difference learning (TD) learning, whereby certain units signal reward prediction errors (RPE). The TD algorithm has been traditionally mapped onto the dopaminergic system, as firing properties of dopamine neurons can resemble RPEs. However, certain predictions of TD learning are inconsistent with experimental results, and previous implementations of the algorithm have made unscalable assumptions regarding stimulus-specific fixed temporal bases. We propose an alternate framework to describe dopamine signaling in the brain, FLEX (Flexibly Learned Errors in Expected Reward). In FLEX, dopamine release is similar, but not identical to RPE, leading to predictions that contrast to those of TD. While FLEX itself is a general theoretical framework, we describe a specific, biophysically plausible implementation, the results of which are consistent with a preponderance of both existing and reanalyzed experimental data.