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Decoding stress vulnerability
Although stress can be considered as an ongoing process that helps an organism to cope with present and future challenges, when it is too intense or uncontrollable, it can lead to adverse consequences for physical and mental health. Social stress specifically, is a highly prevalent traumatic experience, present in multiple contexts, such as war, bullying and interpersonal violence, and it has been linked with increased risk for major depression and anxiety disorders. Nevertheless, not all individuals exposed to strong stressful events develop psychopathology, with the mechanisms of resilience and vulnerability being still under investigation. During this talk, I will identify key gaps in our knowledge about stress vulnerability and I will present our recent data from our contextual fear learning protocol based on social defeat stress in mice.
sensorimotor control, mouvement, touch, EEG
Traditionally, touch is associated with exteroception and is rarely considered a relevant sensory cue for controlling movements in space, unlike vision. We developed a technique to isolate and measure tactile involvement in controlling sliding finger movements over a surface. Young adults traced a 2D shape with their index finger under direct or mirror-reversed visual feedback to create a conflict between visual and somatosensory inputs. In this context, increased reliance on somatosensory input compromises movement accuracy. Based on the hypothesis that tactile cues contribute to guiding hand movements when in contact with a surface, we predicted poorer performance when the participants traced with their bare finger compared to when their tactile sensation was dampened by a smooth, rigid finger splint. The results supported this prediction. EEG source analyses revealed smaller current in the source-localized somatosensory cortex during sensory conflict when the finger directly touched the surface. This finding supports the hypothesis that, in response to mirror-reversed visual feedback, the central nervous system selectively gated task-irrelevant somatosensory inputs, thereby mitigating, though not entirely resolving, the visuo-somatosensory conflict. Together, our results emphasize touch’s involvement in movement control over a surface, challenging the notion that vision predominantly governs goal-directed hand or finger movements.
Top-down control of neocortical threat memory
Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally-generated top-down information reflecting past experiences and current aims. Decades of work have elucidated how sensory neocortex processes physical stimulus features. In contrast, examining how memory-related-top-down information is encoded and integrated with bottom-up signals has long been challenging. Here, I will discuss our recent work pinpointing the outermost layer 1 of neocortex as a central hotspot for processing of experience-dependent top-down information threat during perception, one of the most fundamentally important forms of sensation.
Go with the visual flow: circuit mechanisms for gaze control during locomotion
How the presynapse forms and functions”
Nervous system function relies on the polarized architecture of neurons, established by directional transport of pre- and postsynaptic cargoes. While delivery of postsynaptic components depends on the secretory pathway, the identity of the membrane compartment(s) that supply presynaptic active zone (AZ) and synaptic vesicle (SV) proteins is largely unknown. I will discuss our recent advances in our understanding of how key components of the presynaptic machinery for neurotransmitter release are transported and assembled focussing on our studies in genome-engineered human induced pluripotent stem cell-derived neurons. Specifically, I will focus on the composition and cell biological identity of the axonal transport vesicles that shuttle key components of neurotransmission to nascent synapses and on machinery for axonal transport and its control by signaling lipids. Our studies identify a crucial mechanism mediating the delivery of SV and active zone proteins to developing synapses and reveal connections to neurological disorders. In the second part of my talk, I will discuss how exocytosis and endocytosis are coupled to maintain presynaptic membrane homeostasis. I will present unpublished data regarding the role of membrane tension in the coupling of exocytosis and endocytosis at synapses. We have identified an endocytic BAR domain protein that is capable of sensing alterations in membrane tension caused by the exocytotic fusion of SVs to initiate compensatory endocytosis to restore plasma membrane area. Interference with this mechanism results in defects in the coupling of presynaptic exocytosis and SV recycling at human synapses.
OpenNeuro FitLins GLM: An Accessible, Semi-Automated Pipeline for OpenNeuro Task fMRI Analysis
In this talk, I will discuss the OpenNeuro Fitlins GLM package and provide an illustration of the analytic workflow. OpenNeuro FitLins GLM is a semi-automated pipeline that reduces barriers to analyzing task-based fMRI data from OpenNeuro's 600+ task datasets. Created for psychology, psychiatry and cognitive neuroscience researchers without extensive computational expertise, this tool automates what is largely a manual process and compilation of in-house scripts for data retrieval, validation, quality control, statistical modeling and reporting that, in some cases, may require weeks of effort. The workflow abides by open-science practices, enhancing reproducibility and incorporates community feedback for model improvement. The pipeline integrates BIDS-compliant datasets and fMRIPrep preprocessed derivatives, and dynamically creates BIDS Statistical Model specifications (with Fitlins) to perform common mass univariate [GLM] analyses. To enhance and standardize reporting, it generates comprehensive reports which includes design matrices, statistical maps and COBIDAS-aligned reporting that is fully reproducible from the model specifications and derivatives. OpenNeuro Fitlins GLM has been tested on over 30 datasets spanning 50+ unique fMRI tasks (e.g., working memory, social processing, emotion regulation, decision-making, motor paradigms), reducing analysis times from weeks to hours when using high-performance computers, thereby enabling researchers to conduct robust single-study, meta- and mega-analyses of task fMRI data with significantly improved accessibility, standardized reporting and reproducibility.
Neural control of internal affective states”
“Development and application of gaze control models for active perception”
Gaze shifts in humans serve to direct high-resolution vision provided by the fovea towards areas in the environment. Gaze can be considered a proxy for attention or indicator of the relative importance of different parts of the environment. In this talk, we discuss the development of generative models of human gaze in response to visual input. We discuss how such models can be learned, both using supervised learning and using implicit feedback as an agent interacts with the environment, the latter being more plausible in biological agents. We also discuss two ways such models can be used. First, they can be used to improve the performance of artificial autonomous systems, in applications such as autonomous navigation. Second, because these models are contingent on the human’s task, goals, and/or state in the context of the environment, observations of gaze can be used to infer information about user intent. This information can be used to improve human-machine and human robot interaction, by making interfaces more anticipative. We discuss example applications in gaze-typing, robotic tele-operation and human-robot interaction.
Neural mechanisms of rhythmic motor control in Drosophila
All animal locomotion is rhythmic,whether it is achieved through undulatory movement of the whole body or the coordination of articulated limbs. Neurobiologists have long studied locomotor circuits that produce rhythmic activity with non-rhythmic input, also called central pattern generators (CPGs). However, the cellular and microcircuit implementation of a walking CPG has not been described for any limbed animal. New comprehensive connectomes of the fruit fly ventral nerve cord (VNC) provide an opportunity to study rhythmogenic walking circuits at a synaptic scale.We use a data-driven network modeling approach to identify and characterize a putative walking CPG in the Drosophila leg motor system.
Examining dexterous motor control in children born with a below elbow deficiency
Vision for perception versus vision for action: dissociable contributions of visual sensory drives from primary visual cortex and superior colliculus neurons to orienting behaviors
The primary visual cortex (V1) directly projects to the superior colliculus (SC) and is believed to provide sensory drive for eye movements. Consistent with this, a majority of saccade-related SC neurons also exhibit short-latency, stimulus-driven visual responses, which are additionally feature-tuned. However, direct neurophysiological comparisons of the visual response properties of the two anatomically-connected brain areas are surprisingly lacking, especially with respect to active looking behaviors. I will describe a series of experiments characterizing visual response properties in primate V1 and SC neurons, exploring feature dimensions like visual field location, spatial frequency, orientation, contrast, and luminance polarity. The results suggest a substantial, qualitative reformatting of SC visual responses when compared to V1. For example, SC visual response latencies are actively delayed, independent of individual neuron tuning preferences, as a function of increasing spatial frequency, and this phenomenon is directly correlated with saccadic reaction times. Such “coarse-to-fine” rank ordering of SC visual response latencies as a function of spatial frequency is much weaker in V1, suggesting a dissociation of V1 responses from saccade timing. Consistent with this, when we next explored trial-by-trial correlations of individual neurons’ visual response strengths and visual response latencies with saccadic reaction times, we found that most SC neurons exhibited, on a trial-by-trial basis, stronger and earlier visual responses for faster saccadic reaction times. Moreover, these correlations were substantially higher for visual-motor neurons in the intermediate and deep layers than for more superficial visual-only neurons. No such correlations existed systematically in V1. Thus, visual responses in SC and V1 serve fundamentally different roles in active vision: V1 jumpstarts sensing and image analysis, but SC jumpstarts moving. I will finish by demonstrating, using V1 reversible inactivation, that, despite reformatting of signals from V1 to the brainstem, V1 is still a necessary gateway for visually-driven oculomotor responses to occur, even for the most reflexive of eye movement phenomena. This is a fundamental difference from rodent studies demonstrating clear V1-independent processing in afferent visual pathways bypassing the geniculostriate one, and it demonstrates the importance of multi-species comparisons in the study of oculomotor control.
CNS Control of Peripheral Mitochondrial Form and Function: Mitokines
My laboratory has made an intriguing discovery that mitochondrial stress in one tissue can be communicated to distal tissues. We find that mitochondrial stress in the nervous system triggers the production of entities known as mitokines. These mitokines are discharged from the nervous system, orchestrating a response in peripheral tissues that extends the lifespan of C. elegans. The revelation came as a surprise, given the prevalent belief that cell autonomous mechanisms would underlie the relationship between mitochondrial function and aging. It was also surprising given the prevailing dogma that mitochondrial function must be increased, not decreased, to improve health and longevity. Our work also underscores the fact that mitochondria, which originated as a microbial entity and later evolved into an intracellular symbiont, have retained their capacity for intercommunication, now facilitated by signals from the nervous system. We hypothesize that this communication has evolved as a mechanism to reduce infection from pathogens.
Mouse Motor Cortex Circuits and Roles in Oromanual Behavior
I’m interested in structure-function relationships in neural circuits and behavior, with a focus on motor and somatosensory areas of the mouse’s cortex involved in controlling forelimb movements. In one line of investigation, we take a bottom-up, cellularly oriented approach and use optogenetics, electrophysiology, and related slice-based methods to dissect cell-type-specific circuits of corticospinal and other neurons in forelimb motor cortex. In another, we take a top-down ethologically oriented approach and analyze the kinematics and cortical correlates of “oromanual” dexterity as mice handle food. I'll discuss recent progress on both fronts.
Beyond Homogeneity: Characterizing Brain Disorder Heterogeneity through EEG and Normative Modeling
Electroencephalography (EEG) has been thoroughly studied for decades in psychiatry research. Yet its integration into clinical practice as a diagnostic/prognostic tool remains unachieved. We hypothesize that a key reason is the underlying patient's heterogeneity, overlooked in psychiatric EEG research relying on a case-control approach. We combine HD-EEG with normative modeling to quantify this heterogeneity using two well-established and extensively investigated EEG characteristics -spectral power and functional connectivity- across a cohort of 1674 patients with attention-deficit/hyperactivity disorder, autism spectrum disorder, learning disorder, or anxiety, and 560 matched controls. Normative models showed that deviations from population norms among patients were highly heterogeneous and frequency-dependent. Deviation spatial overlap across patients did not exceed 40% and 24% for spectral and connectivity, respectively. Considering individual deviations in patients has significantly enhanced comparative analysis, and the identification of patient-specific markers has demonstrated a correlation with clinical assessments, representing a crucial step towards attaining precision psychiatry through EEG.
Principles of Cognitive Control over Task Focus and Task
2024 BACN Mid-Career Prize Lecture Adaptive behavior requires the ability to focus on a current task and protect it from distraction (cognitive stability), and to rapidly switch tasks when circumstances change (cognitive flexibility). How people control task focus and switch-readiness has therefore been the target of burgeoning research literatures. Here, I review and integrate these literatures to derive a cognitive architecture and functional rules underlying the regulation of stability and flexibility. I propose that task focus and switch-readiness are supported by independent mechanisms whose strategic regulation is nevertheless governed by shared principles: both stability and flexibility are matched to anticipated challenges via an incremental, online learner that nudges control up or down based on the recent history of task demands (a recency heuristic), as well as via episodic reinstatement when the current context matches a past experience (a recognition heuristic).
Metabolic-functional coupling of parvalbmunin-positive GABAergic interneurons in the injured and epileptic brain
Parvalbumin-positive GABAergic interneurons (PV-INs) provide inhibitory control of excitatory neuron activity, coordinate circuit function, and regulate behavior and cognition. PV-INs are uniquely susceptible to loss and dysfunction in traumatic brain injury (TBI) and epilepsy but the cause of this susceptibility is unknown. One hypothesis is that PV-INs use specialized metabolic systems to support their high-frequency action potential firing and that metabolic stress disrupts these systems, leading to their dysfunction and loss. Metabolism-based therapies can restore PV-IN function after injury in preclinical TBI models. Based on these findings, we hypothesize that (1) PV-INs are highly metabolically specialized, (2) these specializations are lost after TBI, and (3) restoring PV-IN metabolic specializations can improve PV-IN function as well as TBI-related outcomes. Using novel single-cell approaches, we can now quantify cell-type-specific metabolism in complex tissues to determine whether PV-IN metabolic dysfunction contributes to the pathophysiology of TBI.
Cell-type-specific plasticity shapes neocortical dynamics for motor learning
How do cortical circuits acquire new dynamics that drive learned movements? This webinar will focus on mouse premotor cortex in relation to learned lick-timing and explore high-density electrophysiology using our silicon neural probes alongside region and cell-type-specific acute genetic manipulations of proteins required for synaptic plasticity.
Thalamocortical feedback circuits selectively control pyramidal neuron excitability
Unifying the mechanisms of hippocampal episodic memory and prefrontal working memory
Remembering events in the past is crucial to intelligent behaviour. Flexible memory retrieval, beyond simple recall, requires a model of how events relate to one another. Two key brain systems are implicated in this process: the hippocampal episodic memory (EM) system and the prefrontal working memory (WM) system. While an understanding of the hippocampal system, from computation to algorithm and representation, is emerging, less is understood about how the prefrontal WM system can give rise to flexible computations beyond simple memory retrieval, and even less is understood about how the two systems relate to each other. Here we develop a mathematical theory relating the algorithms and representations of EM and WM by showing a duality between storing memories in synapses versus neural activity. In doing so, we develop a formal theory of the algorithm and representation of prefrontal WM as structured, and controllable, neural subspaces (termed activity slots). By building models using this formalism, we elucidate the differences, similarities, and trade-offs between the hippocampal and prefrontal algorithms. Lastly, we show that several prefrontal representations in tasks ranging from list learning to cue dependent recall are unified as controllable activity slots. Our results unify frontal and temporal representations of memory, and offer a new basis for understanding the prefrontal representation of WM
Reimagining the neuron as a controller: A novel model for Neuroscience and AI
We build upon and expand the efficient coding and predictive information models of neurons, presenting a novel perspective that neurons not only predict but also actively influence their future inputs through their outputs. We introduce the concept of neurons as feedback controllers of their environments, a role traditionally considered computationally demanding, particularly when the dynamical system characterizing the environment is unknown. By harnessing a novel data-driven control framework, we illustrate the feasibility of biological neurons functioning as effective feedback controllers. This innovative approach enables us to coherently explain various experimental findings that previously seemed unrelated. Our research has profound implications, potentially revolutionizing the modeling of neuronal circuits and paving the way for the creation of alternative, biologically inspired artificial neural networks.
Seizure control by electrical stimulation: parameters and mechanisms
Seizure suppression by deep brain stimulation (DBS) applies high frequency stimulation (HFS) to grey matter to block seizures. In this presentation, I will present the results of a different method that employs low frequency stimulation (LFS) (1 to 10Hz) of white matter tracts to prevent seizures. The approach has been shown to be effective in the hippocampus by stimulating the ventral and dorsal hippocampal commissure in both animal and human studies respectively for mesial temporal lobe seizures. A similar stimulation paradigm has been shown to be effective at controlling focal cortical seizures in rats with corpus callosum stimulation. This stimulation targets the axons of the corpus callosum innervating the focal zone at low frequencies (5 to 10Hz) and has been shown to significantly reduce both seizure and spike frequency. The mechanisms of this suppression paradigm have been elucidated with in-vitro studies and involve the activation of two long-lasting inhibitory potentials GABAB and sAHP. LFS mechanisms are similar in both hippocampus and cortical brain slices. Additionally, the results show that LFS does not block seizures but rather decreases the excitability of the tissue to prevent seizures. Three methods of seizure suppression, LFS applied to fiber tracts, HFS applied to focal zone and stimulation of the anterior nucleus of the thalamus (ANT) were compared directly in the same animal in an in-vivo epilepsy model. The results indicate that LFS generated a significantly higher level of suppression, indicating LFS of white matter tract could be a useful addition as a stimulation paradigm for the treatment of epilepsy.
Cellular and genetic mechanisms of cerebral cortex folding
One of the most prominent features of the human brain is the fabulous size of the cerebral cortex and its intricate folding, both of which emerge during development. Over the last few years, work from my lab has shown that specific cellular and genetic mechanisms play central roles in cortex folding, particularly linked to neural stem and progenitor cells. Key mechanisms include high rates of neurogenesis, high abundance of basal Radial Glia Cells (bRGCs), and neuron migration, all of which are intertwined during development. We have also shown that primary cortical folds follow highly stereotyped patterns, defined by a spatial-temporal protomap of gene expression within germinal layers of the developing cortex. I will present recent findings from my laboratory revealing novel cellular and genetic mechanisms that regulate cortex expansion and folding. We have uncovered the contribution of epigenetic regulation to the establishment of the cortex folding protomap, modulating the expression levels of key transcription factors that control progenitor cell proliferation and cortex folding. At the single cell level, we have identified an unprecedented diversity of cortical progenitor cell classes in the ferret and human embryonic cortex. These are differentially enriched in gyrus versus sulcus regions and establish parallel cell lineages, not observed in mouse. Our findings show that genetic and epigenetic mechanisms in gyrencephalic species diversify cortical progenitor cell types and implement parallel cell linages, driving the expansion of neurogenesis and patterning cerebral cortex folds.
Soft Discrimination of Healthy Controls and Patients with Mild Cognitive Impairment Based on EEG Data
Astrocyte reprogramming / activation and brain homeostasis
Astrocytes are multifunctional glial cells, implicated in neurogenesis and synaptogenesis, supporting and fine-tuning neuronal activity and maintaining brain homeostasis by controlling blood-brain barrier permeability. During the last years a number of studies have shown that astrocytes can also be converted into neurons if they force-express neurogenic transcription factors or miRNAs. Direct astrocytic reprogramming to induced-neurons (iNs) is a powerful approach for manipulating cell fate, as it takes advantage of the intrinsic neural stem cell (NSC) potential of brain resident reactive astrocytes. To this end, astrocytic cell fate conversion to iNs has been well-established in vitro and in vivo using combinations of transcription factors (TFs) or chemical cocktails. Challenging the expression of lineage-specific TFs is accompanied by changes in the expression of miRNAs, that post-transcriptionally modulate high numbers of neurogenesis-promoting factors and have therefore been introduced, supplementary or alternatively to TFs, to instruct direct neuronal reprogramming. The neurogenic miRNA miR-124 has been employed in direct reprogramming protocols supplementary to neurogenic TFs and other miRNAs to enhance direct neurogenic conversion by suppressing multiple non-neuronal targets. In our group we aimed to investigate whether miR-124 is sufficient to drive direct reprogramming of astrocytes to induced-neurons (iNs) on its own both in vitro and in vivo and elucidate its independent mechanism of reprogramming action. Our in vitro data indicate that miR-124 is a potent driver of the reprogramming switch of astrocytes towards an immature neuronal fate. Elucidation of the molecular pathways being triggered by miR-124 by RNA-seq analysis revealed that miR-124 is sufficient to instruct reprogramming of cortical astrocytes to immature induced-neurons (iNs) in vitro by down-regulating genes with important regulatory roles in astrocytic function. Among these, the RNA binding protein Zfp36l1, implicated in ARE-mediated mRNA decay, was found to be a direct target of miR-124, that be its turn targets neuronal-specific proteins participating in cortical development, which get de-repressed in miR-124-iNs. Furthermore, miR-124 is potent to guide direct neuronal reprogramming of reactive astrocytes to iNs of cortical identity following cortical trauma, a novel finding confirming its robust reprogramming action within the cortical microenvironment under neuroinflammatory conditions. In parallel to their reprogramming properties, astrocytes also participate in the maintenance of blood-brain barrier integrity, which ensures the physiological functioning of the central nervous system and gets affected contributing to the pathology of several neurodegenerative diseases. To study in real time the dynamic physical interactions of astrocytes with brain vasculature under homeostatic and pathological conditions, we performed 2-photon brain intravital imaging in a mouse model of systemic neuroinflammation, known to trigger astrogliosis and microgliosis and to evoke changes in astrocytic contact with brain vasculature. Our in vivo findings indicate that following neuroinflammation the endfeet of activated perivascular astrocytes lose their close proximity and physiological cross-talk with vasculature, however this event is at compensated by the cross-talk of astrocytes with activated microglia, safeguarding blood vessel coverage and maintenance of blood-brain integrity.
CXCL9:SPP1 macrophage polarity identifies a network of cellular programs that control human cancers
Tracking subjects' strategies in behavioural choice experiments at trial resolution
Psychology and neuroscience are increasingly looking to fine-grained analyses of decision-making behaviour, seeking to characterise not just the variation between subjects but also a subject's variability across time. When analysing the behaviour of each subject in a choice task, we ideally want to know not only when the subject has learnt the correct choice rule but also what the subject tried while learning. I introduce a simple but effective Bayesian approach to inferring the probability of different choice strategies at trial resolution. This can be used both for inferring when subjects learn, by tracking the probability of the strategy matching the target rule, and for inferring subjects use of exploratory strategies during learning. Applied to data from rodent and human decision tasks, we find learning occurs earlier and more often than estimated using classical approaches. Around both learning and changes in the rewarded rules the exploratory strategies of win-stay and lose-shift, often considered complementary, are consistently used independently. Indeed, we find the use of lose-shift is strong evidence that animals have latently learnt the salient features of a new rewarded rule. Our approach can be extended to any discrete choice strategy, and its low computational cost is ideally suited for real-time analysis and closed-loop control.
Event-related frequency adjustment (ERFA): A methodology for investigating neural entrainment
Neural entrainment has become a phenomenon of exceptional interest to neuroscience, given its involvement in rhythm perception, production, and overt synchronized behavior. Yet, traditional methods fail to quantify neural entrainment due to a misalignment with its fundamental definition (e.g., see Novembre and Iannetti, 2018; Rajandran and Schupp, 2019). The definition of entrainment assumes that endogenous oscillatory brain activity undergoes dynamic frequency adjustments to synchronize with environmental rhythms (Lakatos et al., 2019). Following this definition, we recently developed a method sensitive to this process. Our aim was to isolate from the electroencephalographic (EEG) signal an oscillatory component that is attuned to the frequency of a rhythmic stimulation, hypothesizing that the oscillation would adaptively speed up and slow down to achieve stable synchronization over time. To induce and measure these adaptive changes in a controlled fashion, we developed the event-related frequency adjustment (ERFA) paradigm (Rosso et al., 2023). A total of twenty healthy participants took part in our study. They were instructed to tap their finger synchronously with an isochronous auditory metronome, which was unpredictably perturbed by phase-shifts and tempo-changes in both positive and negative directions across different experimental conditions. EEG was recorded during the task, and ERFA responses were quantified as changes in instantaneous frequency of the entrained component. Our results indicate that ERFAs track the stimulus dynamics in accordance with the perturbation type and direction, preferentially for a sensorimotor component. The clear and consistent patterns confirm that our method is sensitive to the process of frequency adjustment that defines neural entrainment. In this Virtual Journal Club, the discussion of our findings will be complemented by methodological insights beneficial to researchers in the fields of rhythm perception and production, as well as timing in general. We discuss the dos and don’ts of using instantaneous frequency to quantify oscillatory dynamics, the advantages of adopting a multivariate approach to source separation, the robustness against the confounder of responses evoked by periodic stimulation, and provide an overview of domains and concrete examples where the methodological framework can be applied.
Gut/Body interactions in health and disease
The adult intestine is a major barrier epithelium and coordinator of multi-organ functions. Stem cells constantly repair the intestinal epithelium by adjusting their proliferation and differentiation to tissue intrinsic as well as micro- and macro-environmental signals. How these signals integrate to control intestinal and whole-body homeostasis is largely unknown. Addressing this gap in knowledge is central to an improved understanding of intestinal pathophysiology and its systemic consequences. Combining Drosophila and mammalian model systems my laboratory has discovered fundamental mechanisms driving intestinal regeneration and tumourigenesis and outlined complex inter-organ signaling regulating health and disease. During my talk, I will discuss inter-related areas of research from my lab, including:1- Interactions between the intestine and its microenvironment influencing intestinal regeneration and tumourigenesis. 2- Long-range signals from the intestine impacting whole-body in health and disease.
Predictive processing in older adults: How does it shape perception and sensorimotor control?
The role of CNS microglia in health and disease
Microglia are the resident CNS macrophages of the brain parenchyma. They have many and opposing roles in health and disease, ranging from inflammatory to anti-inflammatory and protective functions, depending on the developmental stage and the disease context. In Multiple Sclerosis, microglia are involved to important hallmarks of the disease, such as inflammation, demyelination, axonal damage and remyelination, however the exact mechanisms controlling their transformation towards a protective or devastating phenotype during the disease progression remains largely unknown until now. We wish to understand how brain microglia respond to demyelinating insults and how their behaviour changes in recovery. To do so we developed a novel histopathological analysis approach in 3D and a cell-based analysis tool that when applied in the cuprizone model of demyelination revealed region- and disease- dependent changes in microglial dynamics in the brain grey matter during demyelination and remyelination. We now use similar approaches with the aim to unravel sensitive changes in microglial dynamics during neuroinflammation in the EAE model. Furthermore, we employ constitutive knockout and tamoxifen-inducible gene-targeting approaches, immunological techniques, genetics and bioinformatics and currently seek to clarify the specific role of the brain resident microglial NF-κB molecular pathway versus other tissue macrophages in EAE.
A recurrent network model of planning predicts hippocampal replay and human behavior
When interacting with complex environments, humans can rapidly adapt their behavior to changes in task or context. To facilitate this adaptation, we often spend substantial periods of time contemplating possible futures before acting. For such planning to be rational, the benefits of planning to future behavior must at least compensate for the time spent thinking. Here we capture these features of human behavior by developing a neural network model where not only actions, but also planning, are controlled by prefrontal cortex. This model consists of a meta-reinforcement learning agent augmented with the ability to plan by sampling imagined action sequences drawn from its own policy, which we refer to as `rollouts'. Our results demonstrate that this agent learns to plan when planning is beneficial, explaining the empirical variability in human thinking times. Additionally, the patterns of policy rollouts employed by the artificial agent closely resemble patterns of rodent hippocampal replays recently recorded in a spatial navigation task, in terms of both their spatial statistics and their relationship to subsequent behavior. Our work provides a new theory of how the brain could implement planning through prefrontal-hippocampal interactions, where hippocampal replays are triggered by -- and in turn adaptively affect -- prefrontal dynamics.
Use of brain imaging data to improve prescriptions of psychotropic drugs - Examples of ketamine in depression and antipsychotics in schizophrenia
The use of molecular imaging, particularly PET and SPECT, has significantly transformed the treatment of schizophrenia with antipsychotic drugs since the late 1980s. It has offered insights into the links between drug target engagement, clinical effects, and side effects. A therapeutic window for receptor occupancy is established for antipsychotics, yet there is a divergence of opinions regarding the importance of blood levels, with many downplaying their significance. As a result, the role of therapeutic drug monitoring (TDM) as a personalized therapy tool is often underrated. Since molecular imaging of antipsychotics has focused almost entirely on D2-like dopamine receptors and their potential to control positive symptoms, negative symptoms and cognitive deficits are hardly or not at all investigated. Alternative methods have been introduced, i.e. to investigate the correlation between approximated receptor occupancies from blood levels and cognitive measures. Within the domain of antidepressants, and specifically regarding ketamine's efficacy in depression treatment, there is limited comprehension of the association between plasma concentrations and target engagement. The measurement of AMPA receptors in the human brain has added a new level of comprehension regarding ketamine's antidepressant effects. To ensure precise prescription of psychotropic drugs, it is vital to have a nuanced understanding of how molecular and clinical effects interact. Clinician scientists are assigned with the task of integrating these indispensable pharmacological insights into practice, thereby ensuring a rational and effective approach to the treatment of mental health disorders, signaling a new era of personalized drug therapy mechanisms that promote neuronal plasticity not only under pathological conditions, but also in the healthy aging brain.
From controlled environments to complex realities: Exploring the interplay between perceived minds and attention
In our daily lives, we perceive things as possessing a mind (e.g., people) or lacking one (e.g., shoes). Intriguingly, how much mind we attribute to people can vary, with real people perceived to have more mind than depictions of individuals, such as photographs. Drawing from a range of research methodologies, including naturalistic observation, mobile eye tracking, and surreptitious behavior monitoring, I discuss how various shades of mind influence human attention and behaviour. The findings suggest the novel concept that overt attention (where one looks) in real-life is fundamentally supported by covert attention (attending to someone out of the corner of one's eye).
Rodents to Investigate the Neural Basis of Audiovisual Temporal Processing and Perception
To form a coherent perception of the world around us, we are constantly processing and integrating sensory information from multiple modalities. In fact, when auditory and visual stimuli occur within ~100 ms of each other, individuals tend to perceive the stimuli as a single event, even though they occurred separately. In recent years, our lab, and others, have developed rat models of audiovisual temporal perception using behavioural tasks such as temporal order judgments (TOJs) and synchrony judgments (SJs). While these rodent models demonstrate metrics that are consistent with humans (e.g., perceived simultaneity, temporal acuity), we have sought to confirm whether rodents demonstrate the hallmarks of audiovisual temporal perception, such as predictable shifts in their perception based on experience and sensitivity to alterations in neurochemistry. Ultimately, our findings indicate that rats serve as an excellent model to study the neural mechanisms underlying audiovisual temporal perception, which to date remains relativity unknown. Using our validated translational audiovisual behavioural tasks, in combination with optogenetics, neuropharmacology and in vivo electrophysiology, we aim to uncover the mechanisms by which inhibitory neurotransmission and top-down circuits finely control ones’ perception. This research will significantly advance our understanding of the neuronal circuitry underlying audiovisual temporal perception, and will be the first to establish the role of interneurons in regulating the synchronized neural activity that is thought to contribute to the precise binding of audiovisual stimuli.
NII Methods (journal club): NeuroQuery, comprehensive meta-analysis of human brain mapping
We will discuss this paper on Neuroquery, a relatively new web-based meta-analysis tool: https://elifesciences.org/articles/53385.pdf. This is different from Neurosynth in that it generates meta-analysis maps using predictive modeling from the string of text provided at the prompt, instead of performing inferential statistics to calculate the overlap of activation from different studies. This allows the user to generate predictive maps for more nuanced cognitive processes - especially for clinical populations which may be underrepresented in the literature compared to controls - and can be useful in generating predictions about where the activity will be for one's own study, and for creating ROIs.
Doubting the neurofeedback double-blind do participants have residual awareness of experimental purposes in neurofeedback studies?
Neurofeedback provides a feedback display which is linked with on-going brain activity and thus allows self-regulation of neural activity in specific brain regions associated with certain cognitive functions and is considered a promising tool for clinical interventions. Recent reviews of neurofeedback have stressed the importance of applying the “double-blind” experimental design where critically the patient is unaware of the neurofeedback treatment condition. An important question then becomes; is double-blind even possible? Or are subjects aware of the purposes of the neurofeedback experiment? – this question is related to the issue of how we assess awareness or the absence of awareness to certain information in human subjects. Fortunately, methods have been developed which employ neurofeedback implicitly, where the subject is claimed to have no awareness of experimental purposes when performing the neurofeedback. Implicit neurofeedback is intriguing and controversial because it runs counter to the first neurofeedback study, which showed a link between awareness of being in a certain brain state and control of the neurofeedback-derived brain activity. Claiming that humans are unaware of a specific type of mental content is a notoriously difficult endeavor. For instance, what was long held as wholly unconscious phenomena, such as dreams or subliminal perception, have been overturned by more sensitive measures which show that degrees of awareness can be detected. In this talk, I will discuss whether we will critically examine the claim that we can know for certain that a neurofeedback experiment was performed in an unconscious manner. I will present evidence that in certain neurofeedback experiments such as manipulations of attention, participants display residual degrees of awareness of experimental contingencies to alter their cognition.
Movement planning as a window into hierarchical motor control
The ability to organise one's body for action without having to think about it is taken for granted, whether it is handwriting, typing on a smartphone or computer keyboard, tying a shoelace or playing the piano. When compromised, e.g. in stroke, neurodegenerative and developmental disorders, the individuals’ study, work and day-to-day living are impacted with high societal costs. Until recently, indirect methods such as invasive recordings in animal models, computer simulations, and behavioural markers during sequence execution have been used to study covert motor sequence planning in humans. In this talk, I will demonstrate how multivariate pattern analyses of non-invasive neurophysiological recordings (MEG/EEG), fMRI, and muscular recordings, combined with a new behavioural paradigm, can help us investigate the structure and dynamics of motor sequence control before and after movement execution. Across paradigms, participants learned to retrieve and produce sequences of finger presses from long-term memory. Our findings suggest that sequence planning involves parallel pre-ordering of serial elements of the upcoming sequence, rather than a preparation of a serial trajectory of activation states. Additionally, we observed that the human neocortex automatically reorganizes the order and timing of well-trained movement sequences retrieved from memory into lower and higher-level representations on a trial-by-trial basis. This echoes behavioural transfer across task contexts and flexibility in the final hundreds of milliseconds before movement execution. These findings strongly support a hierarchical and dynamic model of skilled sequence control across the peri-movement phase, which may have implications for clinical interventions.
Computational models of spinal locomotor circuitry
To effectively move in complex and changing environments, animals must control locomotor speed and gait, while precisely coordinating and adapting limb movements to the terrain. The underlying neuronal control is facilitated by circuits in the spinal cord, which integrate supraspinal commands and afferent feedback signals to produce coordinated rhythmic muscle activations necessary for stable locomotion. I will present a series of computational models investigating dynamics of central neuronal interactions as well as a neuromechanical model that integrates neuronal circuits with a model of the musculoskeletal system. These models closely reproduce speed-dependent gait expression and experimentally observed changes following manipulation of multiple classes of genetically-identified neuronal populations. I will discuss the utility of these models in providing experimentally testable predictions for future studies.
A recurrent network model of planning explains hippocampal replay and human behavior
When interacting with complex environments, humans can rapidly adapt their behavior to changes in task or context. To facilitate this adaptation, we often spend substantial periods of time contemplating possible futures before acting. For such planning to be rational, the benefits of planning to future behavior must at least compensate for the time spent thinking. Here we capture these features of human behavior by developing a neural network model where not only actions, but also planning, are controlled by prefrontal cortex. This model consists of a meta-reinforcement learning agent augmented with the ability to plan by sampling imagined action sequences drawn from its own policy, which we refer to as 'rollouts'. Our results demonstrate that this agent learns to plan when planning is beneficial, explaining the empirical variability in human thinking times. Additionally, the patterns of policy rollouts employed by the artificial agent closely resemble patterns of rodent hippocampal replays recently recorded in a spatial navigation task, in terms of both their spatial statistics and their relationship to subsequent behavior. Our work provides a new theory of how the brain could implement planning through prefrontal-hippocampal interactions, where hippocampal replays are triggered by - and in turn adaptively affect - prefrontal dynamics.
Immunosuppression for Parkinson's disease - a new therapeutic strategy?
Caroline Williams-Gray is a Principal Research Associate in the Department of Clinical Neurosciences, University of Cambridge, and an honorary consultant neurologist specializing in Parkinson’s disease and movement disorders. She leads a translational research group investigating the clinical and biological heterogeneity of PD, with the ultimate goal of developing more targeted therapies for different Parkinson’s subtypes. Her recent work has focused on the theory that the immune system plays a significant role in mediating the heterogeneity of PD and its progression. Her lab is investigating this using blood and CSF -based immune markers, PET neuroimaging and neuropathology in stratified PD cohorts; and she is leading the first randomized controlled trial repurposing a peripheral immunosuppressive drug (azathioprine) to slow the progression of PD.
Auditory input to the basal ganglia; Deep brain stimulation and action-stopping: A cognitive neuroscience perspective on the contributions of fronto-basal ganglia circuits to inhibitory control
On Thursday, May 25th we will host Darcy Diesburg and Mark Richardson. Darcy Diesburg, PhD, is a post-doctoral research fellow at Brown University. She will tell us about “Deep brain stimulation and action-stopping: A cognitive neuroscience perspective on the contributions of fronto-basal ganglia circuits to inhibitory control”. Mark Richardson, MD, PhD, is the Director of Functional Neurosurgery at the Massachusetts General Hospital, Charles Pappas Associate Professor of Neurosciences at Harvard Medical School and Visiting Associate Professor of Brain and Cognitive Sciences at MIT. Beside his scientific presentation on “Auditory input to the basal ganglia”, he will give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!
The role of sub-population structure in computations through neural dynamics
Neural computations are currently conceptualised using two separate approaches: sorting neurons into functional sub-populations or examining distributed collective dynamics. Whether and how these two aspects interact to shape computations is currently unclear. Using a novel approach to extract computational mechanisms from recurrent networks trained on neuroscience tasks, we show that the collective dynamics and sub-population structure play fundamentally complementary roles. Although various tasks can be implemented in networks with fully random population structure, we found that flexible input–output mappings instead require a non-random population structure that can be described in terms of multiple sub-populations. Our analyses revealed that such a sub-population organisation enables flexible computations through a mechanism based on gain-controlled modulations that flexibly shape the collective dynamics.
Feedback control in the nervous system: from cells and circuits to behaviour
The nervous system is fundamentally a closed loop control device: the output of actions continually influences the internal state and subsequent actions. This is true at the single cell and even the molecular level, where “actions” take the form of signals that are fed back to achieve a variety of functions, including homeostasis, excitability and various kinds of multistability that allow switching and storage of memory. It is also true at the behavioural level, where an animal’s motor actions directly influence sensory input on short timescales, and higher level information about goals and intended actions are continually updated on the basis of current and past actions. Studying the brain in a closed loop setting requires a multidisciplinary approach, leveraging engineering and theory as well as advances in measuring and manipulating the nervous system. I will describe our recent attempts to achieve this fusion of approaches at multiple levels in the nervous system, from synaptic signalling to closed loop brain machine interfaces.
Distinct contributions of different anterior frontal regions to rule-guided decision-making in primates: complementary evidence from lesions, electrophysiology, and neurostimulation
Different prefrontal areas contribute in distinctly different ways to rule-guided behaviour in the context of a Wisconsin Card Sorting Test (WCST) analog for macaques. For example, causal evidence from circumscribed lesions in NHPs reveals that dorsolateral prefrontal cortex (dlPFC) is necessary to maintain a reinforced abstract rule in working memory, orbitofrontal cortex (OFC) is needed to rapidly update representations of rule value, and the anterior cingulate cortex (ACC) plays a key role in cognitive control and integrating information for correct and incorrect trials over recent outcomes. Moreover, recent lesion studies of frontopolar cortex (FPC) suggest it contributes to representing the relative value of unchosen alternatives, including rules. Yet we do not understand how these functional specializations relate to intrinsic neuronal activities nor the extent to which these neuronal activities differ between different prefrontal regions. After reviewing the aforementioned causal evidence I will present our new data from studies using multi-area multi-electrode recording techniques in NHPs to simultaneously record from four different prefrontal regions implicated in rule-guided behaviour. Multi-electrode micro-arrays (‘Utah arrays’) were chronically implanted in dlPFC, vlPFC, OFC, and FPC of two macaques, allowing us to simultaneously record single and multiunit activity, and local field potential (LFP), from all regions while the monkey performs the WCST analog. Rule-related neuronal activity was widespread in all areas recorded but it differed in degree and in timing between different areas. I will also present preliminary results from decoding analyses applied to rule-related neuronal activities both from individual clusters and also from population measures. These results confirm and help quantify dynamic task-related activities that differ between prefrontal regions. We also found task-related modulation of LFPs within beta and gamma bands in FPC. By combining this correlational recording methods with trial-specific causal interventions (electrical microstimulation) to FPC we could significantly enhance and impair animals performance in distinct task epochs in functionally relevant ways, further consistent with an emerging picture of regional functional specialization within a distributed framework of interacting and interconnected cortical regions.
Off-policy learning in the basal ganglia
I will discuss work with Jack Lindsey modeling reinforcement learning for action selection in the basal ganglia. I will argue that the presence of multiple brain regions, in addition to the basal ganglia, that contribute to motor control motivates the need for an off-policy basal ganglia learning algorithm. I will then describe a biological implementation of such an algorithm that predicts tuning of dopamine neurons to a quantity we call "action surprise," in addition to reward prediction error. In the same model, an implementation of learning from a motor efference copy also predicts a novel solution to the problem of multiplexing feedforward and efference-related striatal activity. The solution exploits the difference between D1 and D2-expressing medium spiny neurons and leads to predictions about striatal dynamics.
The sense of agency as an explorative role in our perception and action
The sense of agency refers to the subjective feeling of controlling one's own behavior and, through them, external events. Why is this subjective feeling important for humans? Is it just a by-product of our actions? Previous studies have shown that the sense of agency can affect the intensity of sensory input because we predict the input from our motor intention. However, my research has found that the sense of agency plays more roles than just predictions. It enhances perceptual processes of sensory input and potentially helps to harvest more information about the link between the external world and the self. Furthermore, our recent research found both indirect and direct evidence that the sense of agency is important for people's exploratory behaviors, and this may be linked to proximal exploitations of one's control in the environment. In this talk, I will also introduce the paradigms we use to study the sense of agency as a result of perceptual processes, and our findings of individual differences in this sense and the implications.
Establishment and aging of the neuronal DNA methylation landscape in the hippocampus
The hippocampus is a brain region with key roles in memory formation, cognitive flexibility and emotional control. Yet hippocampal function is impaired severely during aging and in neurodegenerative diseases, and impairments in hippocampal function underlie age-related cognitive decline. Accumulating evidence suggests that the deterioration of the neuron-specific epigenetic landscape during aging contributes to their progressive, age-related dysfunction. For instance, we have recently shown that aging is associated with pronounced alterations of neuronal DNA methylation patterns in the hippocampus. Because neurons are generated mostly during development with limited replacement in the adult brain, they are particularly long-lived cells and have to maintain their cell-type specific gene expression programs life-long in order to preserve brain function. Understanding the epigenetic mechanisms that underlie the establishment and long-term maintenance of neuron-specific gene expression programs, will help us to comprehend the sources and consequences of their age-related deterioration. In this talk, I will present our recent work that investigated the role of DNA methylation in the establishment of neuronal gene expression programs and neuronal function, using adult neurogenesis in the hippocampus as a model. I will then describe the effects of aging on the DNA methylation landscape in the hippocampus and discuss the malleability of the aging neuronal methylome to lifestyle and environmental stimulation.
Obesity and Brain – Bidirectional Influences
The regulation of body weight relies on homeostatic mechanisms that use a combination of internal signals and external cues to initiate and terminate food intake. Homeostasis depends on intricate communication between the body and the hypothalamus involving numerous neural and hormonal signals. However, there is growing evidence that higher-level cognitive function may also influence energy balance. For instance, research has shown that BMI is consistently linked to various brain, cognitive, and personality measures, implicating executive, reward, and attentional systems. Moreover, the rise in obesity rates over the past half-century is attributed to the affordability and widespread availability of highly processed foods, a phenomenon that contradicts the idea that food intake is solely regulated by homeostasis. I will suggest that prefrontal systems involved in value computation and motivation act to limit food overconsumption when food is scarce or expensive, but promote over-eating when food is abundant, an optimum strategy from an economic standpoint. I will review the genetic and neuroscience literature on the CNS control of body weight. I will present recent studies supporting a role of prefrontal systems in weight control. I will also present contradictory evidence showing that frontal executive and cognitive findings in obesity may be a consequence not a cause of increased hunger. Finally I will review the effects of obesity on brain anatomy and function. Chronic adiposity leads to cerebrovascular dysfunction, cortical thinning, and cognitive impairment. As the most common preventable risk factor for dementia, obesity poses a significant threat to brain health. I will conclude by reviewing evidence for treatment of obesity in adults to prevent brain disease.
Self-perception: mechanosensation and beyond
Brain-organ communications play a crucial role in maintaining the body's physiological and psychological homeostasis, and are controlled by complex neural and hormonal systems, including the internal mechanosensory organs. However, the progress has been slow due to technical hurdles: the sensory neurons are deeply buried inside the body and are not readily accessible for direct observation, the projection patterns from different organs or body parts are complex rather than converging into dedicate brain regions, the coding principle cannot be directly adapted from that learned from conventional sensory pathways. Our lab apply the pipeline of "biophysics of receptors-cell biology of neurons-functionality of neural circuits-animal behaviors" to explore the molecular and neural mechanisms of self-perception. In the lab, we mainly focus on the following three questions: 1, The molecular and cellular basis for proprioception and interoception. 2, The circuit mechanisms of sensory coding and integration of internal and external information. 3, The function of interoception in regulating behavior homeostasis.
The strongly recurrent regime of cortical networks
Modern electrophysiological recordings simultaneously capture single-unit spiking activities of hundreds of neurons. These neurons exhibit highly complex coordination patterns. Where does this complexity stem from? One candidate is the ubiquitous heterogeneity in connectivity of local neural circuits. Studying neural network dynamics in the linearized regime and using tools from statistical field theory of disordered systems, we derive relations between structure and dynamics that are readily applicable to subsampled recordings of neural circuits: Measuring the statistics of pairwise covariances allows us to infer statistical properties of the underlying connectivity. Applying our results to spontaneous activity of macaque motor cortex, we find that the underlying network operates in a strongly recurrent regime. In this regime, network connectivity is highly heterogeneous, as quantified by a large radius of bulk connectivity eigenvalues. Being close to the point of linear instability, this dynamical regime predicts a rich correlation structure, a large dynamical repertoire, long-range interaction patterns, relatively low dimensionality and a sensitive control of neuronal coordination. These predictions are verified in analyses of spontaneous activity of macaque motor cortex and mouse visual cortex. Finally, we show that even microscopic features of connectivity, such as connection motifs, systematically scale up to determine the global organization of activity in neural circuits.
Controlled sampling of non-equilibrium brain dynamics: modeling and estimation from neuroimaging signals
Bernstein Conference 2024
Deep generative networks as a computational approach for global non-linear control modeling in the nematode C. elegans
Bernstein Conference 2024
Dynamic control of neural manifolds
Bernstein Conference 2024
A feedback control algorithm for online learning in Spiking Neural Networks and Neuromorphic devices
Bernstein Conference 2024
Inhibition-controlled Hebbian learning unifies phenomenological and normative models of plasticity
Bernstein Conference 2024
A neuronal central pattern generator to control the REM/non-REM sleep cycle
Bernstein Conference 2024
Optimal control of oscillations and synchrony in nonlinear models of neural population dynamics
Bernstein Conference 2024
Why spikes? - Analyzing event-based and analog controllers
Bernstein Conference 2024
AutSim: Principled, data driven model development and abstraction for signaling in synaptic protein synthesis in Fragile X Syndrome (FXS) and healthy control.
COSYNE 2022
A control space for muscle state-dependent cortical influence during naturalistic motor behavior
COSYNE 2022
Dynamical systems analysis reveals a novel hypothalamic encoding of state in nodes controlling social behavior
COSYNE 2022
The emergence of gamma oscillations as a signature of gain control during context integration.
COSYNE 2022
Fast ACh signals and the optimal control of attention in a detection task
COSYNE 2022
The geometry of map-like representations under dynamic cognitive control
COSYNE 2022
Goal-directed processing flexibly controls the flow of interhemispheric tactile cues
COSYNE 2022
Goal-directed processing flexibly controls the flow of interhemispheric tactile cues
COSYNE 2022
The geometry of map-like representations under dynamic cognitive control
COSYNE 2022
Identifying the control strategies of monkeys and humans in a virtual balancing task
COSYNE 2022
Identifying the control strategies of monkeys and humans in a virtual balancing task
COSYNE 2022
Inferring implicit sensorimotor costs by inverse optimal control with signal dependent noise
COSYNE 2022
Inferring implicit sensorimotor costs by inverse optimal control with signal dependent noise
COSYNE 2022
An insect vision-based flight control model with a plastic efference copy
COSYNE 2022
An insect vision-based flight control model with a plastic efference copy
COSYNE 2022
Neural Circuit Architectural Priors for Motor Control
COSYNE 2022
Neural Circuit Architectural Priors for Motor Control
COSYNE 2022
The neural code controls the geometry of probabilistic inference in early olfactory processing
COSYNE 2022
The neural code controls the geometry of probabilistic inference in early olfactory processing
COSYNE 2022
Neural optimal feedback control with local learning rules
COSYNE 2022
Neural optimal feedback control with local learning rules
COSYNE 2022
Optimal Multimodal Integration Supports Course Control Under Uncertainty in Walking Drosophila
COSYNE 2022
Optimal Multimodal Integration Supports Course Control Under Uncertainty in Walking Drosophila
COSYNE 2022
Principled credit assignment with strong feedback through Deep Feedback Control
COSYNE 2022
Principled credit assignment with strong feedback through Deep Feedback Control
COSYNE 2022
Serotonergic Control of Model-based Decision Making
COSYNE 2022
Serotonergic Control of Model-based Decision Making
COSYNE 2022
Social cues modulate circuit dynamics to control the choice between communication signals in flies
COSYNE 2022
Soft-actor-critic for model-free reinforcement learning of eye saccade control
COSYNE 2022
Social cues modulate circuit dynamics to control the choice between communication signals in flies
COSYNE 2022
Soft-actor-critic for model-free reinforcement learning of eye saccade control
COSYNE 2022
An Attention-based Multimodal Decoder for Hybrid Brain-Computer Interface Control Systems
Bernstein Conference 2024
control coverage
90 items