Biology subjects

Lam, N. H.

Publications and source records attributed to Lam, N. H..

4 recordsLinked to original sources

bioRxiv2020

Circuit mechanisms of top-down attentional control in a thalamic reticular model

The thalamus engages in attention by amplifying relevant signals and filtering distractors. Whether architectural features of thalamic circuitry offer a unique locus for attentional control is unknown. We developed a circuit model of excitatory thalamocortical and inhibitory reticular neurons, capturing key observations from task-engaged animals. We found that top-down inputs onto reticular neurons regulate thalamic gain effectively, compared to direct thalamocortical inputs. This mechanism enhances downstream readout, improving detection, discrimination, and cross-modal performance. The model revealed heterogeneous thalamic responses that enable decoding top-down versus bottom-up signals. Spiking activity from task-performing mice supported model predictions, with a similar coding geometry in auditory thalamus and readout strategy in auditory cortex. Dynamical systems analysis explained why reticular neurons are potent sites for control, and how lack of excitatory connectivity among thalamocortical neurons enables separation of top-down from bottom-up signals. Our work reveals mechanisms for attentional control and connects circuit architectures to computational functions.

neuroscience↗

bioRxiv2020

A flexible framework for simulating and fitting generalized drift-diffusion models

The drift-diffusion model (DDM) is an important decision-making model in cognitive neuroscience. However, innovations in model form have been limited by methodological challenges. Here, we introduce the generalized drift-diffusion model (GDDM) framework for building, simulating, and fitting DDM extensions, and provide a software package which implements the framework. The GDDM framework augments traditional DDM parameters through arbitrary user-defined functions. Models are simulated numerically by directly solving the Fokker-Planck equation using efficient numerical methods, yielding a 100-fold or greater speedup over standard methodology. This speed allows GDDMs to be fit to data using maximum likelihood on the full response time (RT) distribution. We show that a GDDM fit with our framework explains a classic open dataset with better accuracy and fewer parameters than several DDMs implemented using the latest methodology. Overall, our framework will allow for decision-making model innovation and novel experimental designs.

neuroscience↗

bioRxiv2019

A circuit mechanism for irrationalities in decision-making and NMDA receptor hypofunction: behaviour, computational modelling, and pharmacology

Decision-making biases can be systematic features of normal behaviour, or deficits underlying neuropsychiatric symptoms. We used behavioural psychophysics, spiking-circuit modelling and pharmacological manipulations to explore decision-making biases in health and disease. Monkeys performed an evidence integration task in which they showed a pro-variance bias (PVB): a preference to choose options with more variable evidence. The PVB was also present in a spiking circuit model, revealing a neural mechanism for this behaviour. Because NMDA receptor (NMDA-R) hypofunction is a leading hypothesis for neuropathology in schizophrenia, we simulated behavioural effects of NMDA-R hypofunction onto either excitatory or inhibitory neurons in the model. These were tested experimentally using the NMDA-R antagonist ketamine, yielding changes in decision-making consistent with lowered cortical excitation/inhibition balance from NMDA-R hypofunction onto excitatory neurons. These results provide a circuit-level mechanism that bridges across explanatory scales, from the synaptic to the behavioural, in neuropsychiatric disorders where decision-making biases are prominent.\n\nSignificancePeople can make apparently irrational decisions because of underlying features in their decision circuitry. Deficits in the same neural circuits may also underlie debilitating cognitive symptoms of neuropsychiatric patients. Here, we reveal a neural circuit mechanism explaining an irrationality frequently observed in healthy humans making binary choices - the pro-variance bias. Our circuit model could be perturbed by introducing deficits in either excitatory or inhibitory neuron function. These two perturbations made specific, dissociable predictions for the types of irrational decisionmaking behaviour produced. We used the NMDA-R antagonist ketamine, an experimental model for schizophrenia, to test if these predictions were relevant to neuropsychiatric pathophysiology. The results were consistent with impaired excitatory neuron function, providing important new insights into the pathophysiology of schizophrenia.

neuroscience↗

bioRxiv2017

Effects of altered excitation-inhibition balance on decision making in a cortical circuit model

BackgroundDisruption of the synaptic balance between excitation and inhibition (E/I balance) in cortical circuits is a leading hypothesis for pathophysiologies of neuropsychiatric disorders, such as schizophrenia. However, it is poorly understood how synaptic E/I disruptions propagate upward to induce cognitive deficits, including impaired decision making (DM).\n\nMethodsWe investigated how E/I perturbations may impair temporal integration of evidence during perceptual DM in a biophysically-based model of association cortical microcircuits. Using multiple psychophysical task paradigms, we characterized effects of NMDA receptor hypofunction at two key synaptic sites: inhibitory interneurons (elevating E/I ratio, via disinhibition), versus excitatory pyramidal neurons (lowering E/I ratio).\n\nResultsDisruption of E/I balance in either direction can similarly impair DM as assessed by psychometric performance, following inverted-U dependence. Nonetheless, these regimes make dissociable predictions for task paradigms that characterize the time course of evidence accumulation. Under elevated E/I ratio, DM is impulsive: evidence early in time is weighted much more than late evidence. In contrast, under lowered E/I ratio, DM is indecisive: evidence integration and winner-take-all competition between options are weakened. These effects are well captured by an extended drift-diffusion model with self-coupling.\n\nConclusionsOur findings characterize critical roles of cortical E/I balance in cognitive functions, the utility of timing-sensitive psychophysical paradigms, and relationships between circuit and psychological models. The model makes specific predictions for behavior and neural activity that are testable in humans or animals under causal manipulations of E/I balance and in disease states.

neuroscience↗