Browsing by Author "Twomey, Thomas"
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- Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchangeBatten, Seth R.; Bang, Dan; Kopell, Brian H.; Davis, Arianna N.; Heflin, Matthew; Fu, Qixiu; Perl, Ofer; Ziafa, Kimia; Hashemi, Alice; Saez, Ignacio; Barbosa, Leonardo S.; Twomey, Thomas; Lohrenz, Terry; White, Jason P.; Dayan, Peter; Charney, Alexander W.; Figee, Martijn; Mayberg, Helen S.; Kishida, Kenneth T.; Gu, Xiaosi; Montague, P. Read (Nature Research, 2024-02-26)Dopamine and serotonin are hypothesized to guide social behaviours. In humans, however, we have not yet been able to study neuromodulator dynamics as social interaction unfolds. Here, we obtained subsecond estimates of dopamine and serotonin from human substantia nigra pars reticulata during the ultimatum game. Participants, who were patients with Parkinson’s disease undergoing awake brain surgery, had to accept or reject monetary offers of varying fairness from human and computer players. They rejected more offers in the human than the computer condition, an effect of social context associated with higher overall levels of dopamine but not serotonin. Regardless of the social context, relative changes in dopamine tracked trial-by-trial changes in offer value—akin to reward prediction errors—whereas serotonin tracked the current offer value. These results show that dopamine and serotonin fluctuations in one of the basal ganglia’s main output structures reflect distinct social context and value signals.
- Noradrenaline tracks emotional modulation of attention in human amygdalaBang, Dan; Luo, Yi; Barbosa, Leonardo S.; Batten, Seth R.; Hadj-Amar, Beniamino; Twomey, Thomas; Melville, Natalie; White, Jason P.; Torres, Alexis; Celaya, Xavier; Ramaiah, Priya; McClure, Samuel M.; Brewer, Gene A.; Bina, Robert W.; Lohrenz, Terry; Casas, Brooks; Chiu, Pearl H.; Vannucci, Marina; Kishida, Kenneth T.; Witcher, Mark R.; Montague, P. Read (Elsevier, 2023-11-20)The noradrenaline (NA) system is one of the brain’s major neuromodulatory systems; it originates in a small midbrain nucleus, the locus coeruleus (LC), and projects widely throughout the brain. The LC-NA system is believed to regulate arousal and attention and is a pharmacological target in multiple clinical conditions. Yet our understanding of its role in health and disease has been impeded by a lack of direct recordings in humans. Here, we address this problem by showing that electrochemical estimates of sub-second NA dynamics can be obtained using clinical depth electrodes implanted for epilepsy monitoring. We made these recordings in the amygdala, an evolutionarily ancient structure that supports emotional processing, and receives dense LC-NA projections, while patients (n = 3) performed a visual affective oddball task. The task was designed to induce different cognitive states, with the oddball stimuli involving emotionally evocative images, which varied in terms of arousal (low versus high) and valence (negative versus positive). Consistent with theory, the NA estimates tracked the emotional modulation of attention, with a stronger oddball response in a high-arousal state. Parallel estimates of pupil dilation, a common behavioral proxy for LC-NA activity, supported a hypothesis that pupil-NA coupling changes with cognitive state, with the pupil and NA estimates being positively correlated for oddball stimuli in a high-arousal but not a lowarousal state. Our study provides proof of concept that neuromodulator monitoring is now possible using depth electrodes in standard clinical use.
- On the Characterization of the Performance-Productivity Gap for FPGAGondhalekar, Atharva; Twomey, Thomas; Feng, Wu-chun (IEEE, 2022)Today, FPGA vendors provide a C++/C-based programming environment to enhance programmer productivity over using a hardware-description language at the register-transfer level. The common perception is that this enhanced pro-ductivity comes at the expense of significantly less performance, e.g., as much an order of magnitude worse. To characterize this performance-productivity tradeoff, we propose a new composite metric, II, that quantitatively captures the perceived discrepancy between the performance and productivity of any two given FPGA programming languages, e.g., Verilog vs. OpenCL. We then present the implications of our metric via a case study on the design of a Sobel filter (i.e., edge detector) using three different programming models - Verilog, OpenCL, oneAPI - on an Intel Arria 10 GX FPGA accelerator. Relative to performance, our results show that an optimized OpenCL kernel achieves 84% of the performance of an optimized Verilog version of the code on a 7680×4320 (8K) image. Conversely, relative to productivity, OpenCL offers a 6.1 x improvement in productivity over Verilog, while oneAPI improves the productivity by an additional factor of 1.25 x over OpenCL.