Biology subjects

Sit, T. P.

Publications and source records attributed to Sit, T. P..

5 recordsLinked to original sources

bioRxiv2026

Dissociable norepinephrine and dopamine representations during strategic decision-making and reward learning

Adaptive decision-making in competitive environments requires learning from immediate reward outcomes while tracking longer-timescale information to adjust behavioural strategies and remain unpredictable against others. Dopamine (DA) and norepinephrine (NE) have long been implicated in reward-guided behaviours, but their contributions to strategic choice remain unclear. We trained mice to play a zero-sum matching pennies game against a computer opponent that exploited regularities in their choice and reward history, such that optimal performance required stochastic choice decoupled from immediate reward. We combined fibre photometry recordings, behavioural and neural modelling, and a within-subject multi-task design to determine how NE and DA contribute to strategic choice in the matching pennies game versus reward-guided behaviour in a two-armed bandit (2AB) task. DA responses were dominated by trial-by-trial reward outcomes and consistently tracked model-derived reward prediction errors (RPE) across tasks and behavioural states. In contrast, NE activity reflected salient task events, predicted upcoming choice switches, and tracked longer-timescale variables including model-inferred behavioural strategy and average reward rate. In addition, NE responses were selectively enhanced following rewarded switches when these outcomes were informative for deciding whether to stay in or switch from the current strategy; and this enhancement could not be explained by RPE. Incorporating pre-choice NE activity into a reinforcement-learning model to modulate choice generation improved model prediction in matching pennies but not in the 2AB task. Together, these findings reveal complementary neuromodulatory correlates of competitive decision-making across timescales: DA primarily guides learning from immediate outcomes through RPE, whereas NE additionally represents contextual information and choice stochasticity relevant for shaping long-term strategies.

neuroscience↗

bioRxiv2026

Behavioural and neural mechanisms for stochastic choices in mixed strategy games

Adaptive behaviour usually requires exploiting regularities in the environment, but in competitive settings the opposite can be true: predictable choice patterns can be exploited by others, making unpredictability itself advantageous. How neural circuits generate such strategic variability remains poorly understood. Here, we trained mice to play a zero-sum game against an opponent that exploited statistical regularities in their choices and rewards, and tracked their behaviour and dorsal cortical dynamics across learning. Using a hidden Markov model, we found that mice transitioned from structured, predictable strategies towards a near-optimal stochastic strategy as they learned. Applying the same framework to monkeys playing the same game identified a shared stochastic strategy across species, despite differences in how it was deployed. Cortex-wide imaging revealed that stochastic choices were associated with reduced representation of reward history, while immediate reward signals remained robust. Critically, while the strength of cortical reward signals predicted subsequent choice during reward-guided behaviour, this relationship was abolished during stochastic behaviour. Thus, adaptive stochasticity does not simply arise from a loss of reward information, but from selectively decoupling reward from future choice. These results reveal a neural mechanism through which animals suppress otherwise useful reward-guided structure to generate adaptive unpredictability in competitive environments.

neuroscience↗

bioRxiv2024

MEA-NAP compares microscale functional connectivity, topology, and network dynamics in organoid or monolayer neuronal cultures

Microelectrode array (MEA) recordings are commonly used to compare firing and burst rates in neuronal cultures. MEA recordings can also reveal microscale functional connectivity, topology, and network dynamics--patterns seen in brain networks across spatial scales. Network topology is frequently characterized in neuroimaging with graph theoretical metrics. However, few computational tools exist for analyzing microscale functional brain networks from MEA recordings. Here, we present a MATLAB MEA network analysis pipeline (MEA-NAP) for raw voltage time-series acquired from single- or multi-well MEAs. Applications to 3D human cerebral organoids or 2D human-derived or murine cultures reveal differences in network development, including topology, node cartography, and dimensionality. MEA-NAP incorporates multi-unit template-based spike detection, probabilistic thresholding for determining significant functional connections, and normalization techniques for comparing networks. MEA-NAP can identify network-level effects of pharmacologic perturbation and/or disease-causing mutations and, thus, can provide a translational platform for revealing mechanistic insights and screening new therapeutic approaches.

neuroscience↗

bioRxiv2021

Behavioral origin of sound-evoked activity in visual cortex

Sensory cortices can be affected by stimuli of multiple modalities and are thus increasingly thought to be multisensory. For instance, primary visual cortex (V1) is influenced not only by images but also by sounds. Here we show that the activity evoked by sounds in V1 is highly stereotyped across neurons and even across mice. It resembles activity measured elsewhere in the brain and is independent of projections from auditory cortex. Its low-dimensional nature starkly contrasts the high dimensional code that V1 uses to represent images. Furthermore, this sound-evoked activity can be precisely predicted by small body movements that are elicited by each sound and are highly stereotyped across trials and across mice. Thus, neural activity that is apparently multisensory may simply arise from low-dimensional signals associated with changes in internal state and behavior.

neuroscience↗

bioRxiv2021

The role of frontal cortex in multisensory decisions

To make accurate perceptual decisions, the brain often combines information across sensory modalities. For instance, localizing objects by integrating their image and sound. However, the cortical substrates underlying this audiovisual integration remain uncertain. Here, we show that mouse frontal cortex combines auditory and visual evidence; that this combination is additive, mirroring behavior; and that it evolves with learning. Scanning optogenetic inactivation demonstrated that inactivating frontal cortex impaired choices based on either sensory modality. Recordings from >10,000 neurons indicated that after task learning, activity in frontal area MOs (secondary motor cortex) encodes an additive combination of visual and auditory signals, consistent with the mices behavioral strategy. An accumulator model applied to these sensory representations reproduced both the observed choices and reaction times. These results indicate that frontal cortex adapts through learning to combine evidence across sensory cortices, providing a signal that is transformed into a binary decision by a downstream accumulator.

neuroscience↗