Biology subjects

Averbeck, B. B.

Publications and source records attributed to Averbeck, B. B..

15 recordsLinked to original sources

bioRxiv2026

Consensus across limbic areas predicts motivational disengagement

AbstractMotivational disengagement is widely attributed to low expected reward, yet animals and humans disengage even when reward expectations are constant. This implies a latent mechanism beyond reward. After accounting for expected reward, we found a neural signal across multiple limbic areas that predicted disengagement. As animals disengaged, neural activity across areas converged onto a shared, low-dimensional axis. Consensus across areas predicted whether disengagement persisted, suggesting why single brain area perturbations have produced inconsistent effects. We showed that engagement and disengagement operated as distinct attractor states whose strength scaled with expected reward, revealing that value modulates, but does not determine, motivational state. These findings reframe motivation as a collective computation and suggest that effective interventions for motivational deficits may require targeting multiple areas simultaneously.

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bioRxiv2026

Embodied reinforcement learning in the primate cortico-basal ganglia system

Learning the value of environmental stimuli from reward experience allows animals to make advantageous choices. Existing biological accounts of reinforcement learning (RL) often assume that this value is represented as a single, motor-system-invariant neural signal. Here we recorded neuronal activity across eight nodes of the macaque cortico-basal ganglia system -- from limbic to neocortical regions -- while monkeys learned stimulus-reward associations using either saccades or reaches as the required motor response. The geometry of population activity revealed largely distinct value-coding dimensions for saccades and reaches, including in limbic regions typically associated with motor-system-invariant value coding. Consequently, value information was substantially reduced when read out across motor systems. These results provide circuit-wide evidence that challenges existing neural implementations of RL. They link biological accounts of value learning to embodied frameworks in cognitive science and artificial intelligence, in which behavior is grounded in an agents physical structure rather than abstracted from it.

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bioRxiv2026

Synaptic pruning, myelination and the emergence of psychiatric disorders in late adolescence

Adolescence is an important developmental period during which there are diverse changes in the brain and behavior. Goal-directed behaviors and the component processes underlying those behaviors improve during adolescence, including working memory, response inhibition, and reinforcement learning. At the same time there is substantial pruning of excitatory connections in prefrontal cortex and ongoing myelination of axons. However, psychiatric disorders also become increasingly prevalent in late adolescence and early adulthood. In this study, we develop computational models that suggest a hypothesis for how the ongoing changes in the brain can give rise to the increased prevalence of psychiatric disorders. We show that both myelination and pruning during adolescence lead to attractor landscapes in which strongly encoded memories, driven by three-factor learning rules that modulate Hebbian plasticity, come to dominate the landscape of brain activity, at the expense of weakly encoded memories. Pruning and myelination lead to large, strong attractors which, if they are related to aversive emotions, can drive intrusive thoughts and compulsions in obsessive compulsive disorder, rumination in depression, and aversive memories in post-traumatic stress disorder. The link between pruning, myelination and the emergence of dominant attractors for emotionally salient memories is well supported by the models. The way these effects map onto forebrain circuits requires more work.

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bioRxiv2026

Retrograde transduction of dopaminergic cells in substantia nigra of rhesus monkey

Neuromodulatory systems regulate neural circuits across broad regions of the brain, and disruption of the dopaminergic system contributes to psychiatric and neurodegenerative disorders. Engineered viral vectors have been used to target the neuromodulatory systems of the nonhuman primate brain (Y. Chen et al., 2023; El-Shamayleh et al., 2016; Gray et al., 2010; Lerchner et al., 2014; Perez et al., 2022). However, a conspicuous obstacle to the isolation and modulation of specific pathways is the inability of many retrogradely infecting viruses to transduce dopaminergic (DA) cells efficiently (Tervo et al., 2016; Cushnie et al., 2020; Weiss et al., 2020). We compare the DA neuron retrograde transduction efficacy of four viral vectors after injection into the striatum of nonhuman primates (NHP). Selectivity was assessed by comparing the neuronal co-expression of fluorescent reporter protein and tyrosine-hydroxylase (TH) antibody in substantia nigra pars compacta (SNc). The rabies pseudotyped lentiviral vector, FuG-B2, produced superior retrograde transduction of DA cells to FuG-C or FuG-E. AAV2.retro was the least effective.

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bioRxiv2025

Discrete interneuron subsets participate in GluN1/GluN3A excitatory glycine receptor (eGlyR)-mediated regulation of hippocampal network activity throughout development and evolution.

Decades of studies implicating GluN3A N-methyl-D-aspartate receptor (NMDAR) subunits in physiological and pathological function have largely been interpreted through direct regulation of conventional glutamatergic NMDARs. However, emerging evidence indicates that GluN3A frequently assembles with GluN1 forming unconventional glutamate-insensitive NMDARs that operate as native excitatory glycine receptors (eGlyRs). Here we demonstrate that hippocampal somatostatin and neurogliaform interneurons (Sst-INs and NGFCs) express functional eGlyRs from early postnatal through adult ages. In the developing hippocampus eGlyR-mediated excitation of NGFCs with ambient glycine dramatically increases GABAergic tone, with consequences for the generation of giant depolarizing potentials (GDPs). In the mature hippocampus, eGlyR- mediated excitation of Sst-INs regulates sharp wave ripples (SWRs). Finally, we reveal evolutionary conservation of hippocampal Sst-IN eGlyRs and eGlyR- mediated SWR regulation in non-human primates confirming functional eGlyR availability for therapeutic potential in higher species. Our findings underscore that eGlyR mediated regulation of cell and circuit excitability through both cell autonomous and cell non-autonomous mechanisms must be considered to understand GluN3A roles in brain development, plasticity, and disease.

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bioRxiv2025

A synaptic mechanism for encoding the learned value of action-derived safety

Motivated behavior is often framed in terms of biologically grounded outcomes, such as food or threat. Yet many motivated actions, like the pursuit of safety or agency, depend on outcomes that lack explicit sensory value and must instead be inferred from experience. Here, we identify a thalamostriatal circuit mechanism by which such internally constructed outcomes acquire motivational value. In mice performing an active avoidance task, neurons in the paraventricular thalamus (PVT) projecting to the nucleus accumbens (NAc) develop a safety-encoding signal that emerges following successful avoidance. This signal is experience-dependent and value-sensitive, diminishing upon devaluation of the instrumental contingency. Selective silencing of the PVT[->]NAc projection at safety onset disrupts avoidance persistence without impairing action-outcome learning, as confirmed by computational modeling of value updating based on prediction error. Mechanistically, PVT input recruits cholinergic interneurons (CINs) to modulate dopamine release and this influence depends on synaptic potentiation mediated by GluA2-lacking AMPA receptor insertion at PVT-CIN synapses. Disrupting this plasticity selectively impairs the avoidance response by blunting the motivational value of safety without affecting acquisition. These findings reveal how thalamic circuits assign value to abstract, internal outcomes, providing a framework for understanding how goals like safety are inferred, stabilized, and rendered behaviorally effective.

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bioRxiv2025

A novel, evolutionarily conserved inhibitory circuit selectively regulates dentate gyrus mossy cell function.

The mammalian dentate gyrus contributes to mnemonic function by parsing similar events and places. The disparate activity patterns of mossy cells and granule cells is believed to enable this function yet the mechanisms that drive this circuit dynamic remain elusive. We identified a novel inhibitory interneuron subtype, characterized by VGluT3 expression, with overwhelming target selectivity for mossy cells while also revealing that CCK, PV, SOM and VIP interneurons preferentially innervate granule cells. Leveraging pharmacology and novel enhancer viruses, we find that this target-specific inhibitory innervation pattern is evolutionarily conserved in non-human primates and humans. In addition, in vivo chemogenetic manipulation of VGluT3+ interneurons selectively alters the activity and functional properties of mossy cells. These findings establish that mossy cells and granule cells have unique, evolutionarily conserved inhibitory innervation patterns and suggest selective inhibitory circuits may be necessary to maintain DG circuit dynamics and enable pattern separation across species.

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bioRxiv2024

An enhancer-AAV toolbox to target and manipulate distinct interneuron subtypes

In recent years, we and others have identified a number of enhancers that, when incorporated into rAAV vectors, can restrict the transgene expression to particular neuronal populations. Yet, viral tools to access and manipulate specific neuronal subtypes are still limited. Here, we performed systematic analysis of single cell genomic data to identify enhancer candidates for each of the telencephalic interneuron subtypes. We established a set of enhancer-AAV tools that are highly specific for distinct cortical interneuron populations and striatal cholinergic interneurons. These enhancers, when used in the context of different effectors, can target (fluorescent proteins), observe activity (GCaMP) and manipulate (opto-genetics) specific neuronal subtypes. We also validated our enhancer-AAV tools across species. Thus, we provide the field with a powerful set of tools to study neural circuits and functions and to develop precise and targeted therapy.

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bioRxiv2024

Network computations underlying learning from symbolic gains and losses

Reinforcement learning (RL), particularly in primates, is often driven by symbolic outcomes. However, it is usually studied with primary reinforcers. To examine the neural mechanisms underlying learning from symbolic outcomes, we trained monkeys on a task in which they learned to choose options that led to gains of tokens and avoid choosing options that led to losses of tokens. We then recorded simultaneously from the orbitofrontal cortex (OFC), ventral striatum (VS), amygdala (AMY), and the mediodorsal thalamus (MDt). We found that the OFC played a dominant role in coding token outcomes and token prediction errors. The other areas contributed complementary functions with the VS coding appetitive outcomes and the AMY coding the salience of outcomes. The MDt coded actions and relayed information about tokens between the OFC and VS. Thus, OFC leads the process of symbolic reinforcement learning in the ventral frontostriatal circuitry.

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bioRxiv2024

Divergent opioid-mediated suppression of inhibition between hippocampus and neocortex across species and development

Within the adult rodent hippocampus, opioids suppress inhibitory parvalbumin-expressing interneurons (PV-INs), thus disinhibiting local micro-circuits. However, it is unknown if this disinhibitory motif is conserved in other cortical regions, species, or across development. We observed that PV-IN mediated inhibition is robustly suppressed by opioids in hippocampus proper but not primary neocortex in mice and nonhuman primates, with spontaneous inhibitory tone in resected human tissue also following a consistent dichotomy. This hippocampal disinhibitory motif was established in early development when PV-INs and opioids were found to regulate early population activity. Acute opioid-mediated modulation was partially occluded with morphine pretreatment, with implications for the effects of opioids on hippocampal network activity important for learning and memory. Together, these findings demonstrate that PV-INs exhibit a divergence in opioid sensitivity across brain regions that is remarkably conserved across evolution and highlights the underappreciated role of opioids acting through immature PV-INs in shaping hippocampal development.

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bioRxiv2022

Fast-synaptic axo-axonal transmission from striatal cholinergic interneurons onto dopamine fibers.

Transmission from striatal cholinergic interneurons (CINs) controls dopamine release through nicotinic acetylcholine receptors (nAChRs) on dopaminergic axons. Anatomical studies suggest that cholinergic terminals signal predominantly through non-synaptic volume transmission. However, the influence of cholinergic transmission on electrical signaling in axons remains unclear. We examined axo-axonal transmission from CINs onto dopaminergic axons using perforated-patch recordings which revealed rapid spontaneous EPSPs with properties characteristic of fast synapses. Pharmacology showed that axonal EPSPs (axEPSPs) were mediated primarily by high-affinity 6-containing receptors. Remarkably, axEPSPs triggered spontaneous action potentials locally in dopaminergic axons, suggesting these axons perform integration to convert synaptic input into spiking, a function associated with somatodendritic compartments. We investigated cross-species validity of cholinergic axo-axonal transmission by recording dopaminergic axons in macaque putamen and found similar axEPSPs. Thus, we reveal that fast synaptic-like neurotransmission underlies cholinergic signaling onto dopaminergic axons, providing insight into how nicotinic receptors shape electrical signaling directly in axon terminals.

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bioRxiv2020

Correlates of auditory decision making in prefrontal, auditory, and basal lateral amygdala cortical areas

Auditory selective listening and decision making underlies important processes, including attending to a single speaker in a crowded room, often referred to as the cocktail party problem. To examine the neural mechanisms underlying these behaviors, we developed a novel auditory selective listening paradigm for monkeys. In this task, monkeys had to detect a difficult to discriminate target embedded in noise when presented in a pre-cued location (either left or right) and ignore it if it was in the opposite location. While the animals carried out the task we recorded neural activity in primary auditory cortex (AC), dorsal lateral prefrontal cortex (dlPFC) and the basal lateral amygdala (BLA), given that these areas have been implicated in auditory decision making, selective listing, and/or reward-guided decision making. There were two main findings in the neural data. First, primary AC encoded the side of the cue and target, and the monkeys choice, before either dlPFC or the amygdala. The BLA encoded cue and target variables negligibly, but was engaged at the time of the monkeys choice. Second, decoding analyses suggested that errors followed primarily from a failure to encode the target stimulus in both AC and PFC, but earlier in AC. Thus, AC neural activity is poised to represent the sensory volley and decision making during selective listening before dlPFC, and they both precede activity in BLA.

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bioRxiv2020

CoNNECT: Convolutional Neural Network for Estimating synaptic Connectivity from spike Trains

The recent increase in reliable, simultaneous high channel count extracellular recordings is exciting for physiologists and theoreticians because it offers the possibility of reconstructing the underlying neuronal circuits. We recently presented a method of inferring this circuit connectivity from neuronal spike trains by applying the generalized linear model to cross-correlograms. Although the algorithm can do a good job of circuit reconstruction, the parameters need to be carefully tuned for each individual dataset. Here we present another method using a Convolutional Neural Network for Estimating synaptic Connectivity from spike trains (CoNNECT). After adaptation to huge amounts of simulated data, this method robustly captures the specific feature of monosynaptic impact in a noisy cross-correlogram. There are no user-adjustable parameters. With this new method, we have constructed diagrams of neuronal circuits recorded in several cortical areas of monkeys.

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bioRxiv2019

Dimensionality, information and learning in prefrontal cortex

Learning leads to changes in population patterns of neural activity. In this study we wanted to examine how these changes in patterns of activity affect the dimensionality of neural responses and information about choices. We addressed these questions by carrying out high channel count recordings in dorsal-lateral prefrontal cortex (dlPFC; 768 electrodes) while monkeys performed a two-armed bandit reinforcement learning task. The high channel count recordings allowed us to study population coding while monkeys learned choices between actions or objects. We found that the dimensionality of neural population activity was higher across blocks in which animals learned the values of novel pairs of objects, than across blocks in which they learned the values of actions. The increase in dimensionality with learning in object blocks was related to less shared information across blocks, and therefore patterns of neural activity that were less similar, when compared to learning in action blocks. Furthermore, these differences emerged with learning, and were not a simple function of the choice of a visual image or action. Therefore, learning the values of novel objects increases the dimensionality of neural representations in dlPFC.

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bioRxiv2018

Distinct cross-frequency coupling signatures for top-down and bottom-up information processing in auditory cortex

Predictive coding is a theoretical framework that provides a functional interpretation of top-down and bottom up interactions in sensory processing. The theory has suggested that specific frequency bands relay bottom-up and top-down information (e.g. \"{gamma} up, {beta} down\"). But it remains unclear whether this notion generalizes to cross-frequency interactions. Furthermore, most of the evidence so far comes from visual pathways. Here we examined cross-frequency coupling across four sectors of the auditory hierarchy in the macaque. We computed two measures of cross-frequency coupling, phase-amplitude coupling (PAC) and amplitude-amplitude coupling (AAC). Our findings revealed distinct patterns for bottom-up and top-down information processing among cross-frequency interactions. Both top-down and bottom-up made prominent use of low frequencies: low-to-low frequency ({theta}, , {beta}) and low frequency-to-high {gamma} couplings were predominant top-down, while low frequency-to-low {gamma} couplings were predominant bottom-up. These patterns were largely preserved across coupling types (PAC and AAC) and across stimulus types (natural and synthetic auditory stimuli), suggesting they are a general feature of information processing in auditory cortex. Moreover, our findings showed that low-frequency PAC alternated between predominantly top-down or bottom-up over time. Altogether, this suggests sensory information need not be propagated along separate frequencies upwards and downwards. Rather, information can be unmixed by having low frequencies couple to distinct frequency ranges in the target region, and by alternating top-down and bottom-up processing over time.\n\n1 SignificanceThe brain consists of highly interconnected cortical areas, yet the patterns in directional cortical communication are not fully understood, in particular with regards to interactions between different signal components across frequencies. We employed a a unified, computationally advantageous Granger-causal framework to examine bi-directional cross-frequency interactions across four sectors of the auditory cortical hierarchy in macaques. Our findings extend the view of cross-frequency interactions in auditory cortex, suggesting they also play a prominent role in top-down processing. Our findings also suggest information need not be propagated along separate channels up and down the cortical hierarchy, with important implications for theories of information processing in the brain such as predictive coding.

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