Toward an Integrative Theory of Thalamic Function.

The thalamus has long been suspected to have an important role in cognition, yet recent theories have favored a more corticocentric view. According to this view, the thalamus is an excitatory feedforward relay to or between cortical regions, and cognitively relevant computations are exclusively cortical. Here, we review anatomical, physiological, and behavioral studies along evolutionary and theoretical dimensions, arguing for essential and unique thalamic computations in cognition. Considering their architectural features as well as their ability to initiate, sustain, and switch cortical activity, thalamic circuits appear uniquely suited for computing contextual signals that rapidly reconfigure task-relevant cortical representations. We introduce a framework that formalizes this notion, show its consistency with several findings, and discuss its prediction of thalamic roles in perceptual inference and behavioral flexibility. Overall, our framework emphasizes an expanded view of the thalamus in cognitive computations and provides a roadmap to test several of its theoretical and experimental predictions.

Reliable Sensory Processing in Mouse Visual Cortex through Cooperative Interactions between Somatostatin and Parvalbumin Interneurons.

Intrinsic neuronal variability significantly limits information encoding in the primary visual cortex (V1). However, under certain conditions, neurons can respond reliably with highly precise responses to the same visual stimuli from trial to trial. This suggests that there exists intrinsic neural circuit mechanisms that dynamically modulate the intertrial variability of visual cortical neurons. Here, we sought to elucidate the role of different inhibitory interneurons (INs) in reliable coding in mouse V1. To study the interactions between somatostatin-expressing interneurons (SST-INs) and parvalbumin-expressing interneurons (PV-INs), we used a dual-color calcium imaging technique that allowed us to simultaneously monitor these two neural ensembles while awake mice, of both sexes, passively viewed natural movies. SST neurons were more active during epochs of reliable pyramidal neuron firing, whereas PV neurons were more active during epochs of unreliable firing. SST neuron activity lagged that of PV neurons, consistent with a feedback inhibitory SST→PV circuit. To dissect the role of this circuit in pyramidal neuron activity, we used temporally limited optogenetic activation and inactivation of SST and PV interneurons during periods of reliable and unreliable pyramidal cell firing. Transient firing of SST neurons increased pyramidal neuron reliability by actively suppressing PV neurons, a proposal that was supported by a rate-based model of V1 neurons. These results identify a cooperative functional role for the SST→PV circuit in modulating the reliability of pyramidal neuron activity.SIGNIFICANCE STATEMENT Cortical neurons often respond to identical sensory stimuli with large variability. However, under certain conditions, the same neurons can also respond highly reliably. The circuit mechanisms that contribute to this modulation remain unknown. Here, we used novel dual-wavelength calcium imaging and temporally selective optical perturbation to identify an inhibitory neural circuit in visual cortex that can modulate the reliability of pyramidal neurons to naturalistic visual stimuli. Our results, supported by computational models, suggest that somatostatin interneurons increase pyramidal neuron reliability by suppressing parvalbumin interneurons via the inhibitory SST→PV circuit. These findings reveal a novel role of the SST→PV circuit in modulating the fidelity of neural coding critical for visual perception.

Astrocyte glutamate uptake coordinates experience-dependent, eye-specific refinement in developing visual cortex.

The uptake of glutamate by astrocytes actively shapes synaptic transmission, however its role in the development and plasticity of neuronal circuits remains poorly understood. The astrocytic glutamate transporter, GLT1 is the predominant source of glutamate clearance in the adult mouse cortex. Here, we examined the structural and functional development of the visual cortex in GLT1 heterozygous (HET) mice using two-photon microscopy, immunohistochemistry and slice electrophysiology. We find that though eye-specific thalamic axonal segregation is intact, binocular refinement in the primary visual cortex is disrupted. Eye-specific responses to visual stimuli in GLT1 HET mice show altered binocular matching, with abnormally high responses to ipsilateral compared to contralateral eye stimulation and a greater mismatch between preferred orientation selectivity of ipsilateral and contralateral eye responses. Furthermore, we observe an increase in dendritic spine density in the basal dendrites of layer 2/3 excitatory neurons suggesting aberrant spine pruning. Monocular deprivation induces atypical ocular dominance plasticity in GLT1 HET mice, with an unusual depression of ipsilateral open eye responses; however, this change in ipsilateral responses correlates well with an upregulation of GLT1 protein following monocular deprivation. These results demonstrate that a key function of astrocytic GLT1 function during development is the experience-dependent refinement of ipsilateral eye inputs relative to contralateral eye inputs in visual cortex.

Jointly reduced inhibition and excitation underlies circuit-wide changes in cortical processing in Rett syndrome.

Rett syndrome (RTT) arises from loss-of-function mutations in methyl-CpG binding protein 2 gene (Mecp2), but fundamental aspects of its physiological mechanisms are unresolved. Here, by whole-cell recording of synaptic responses in MeCP2 mutant mice in vivo, we show that visually driven excitatory and inhibitory conductances are both reduced in cortical pyramidal neurons. The excitation-to-inhibition (E/I) ratio is increased in amplitude and prolonged in time course. These changes predict circuit-wide reductions in response reliability and selectivity of pyramidal neurons to visual stimuli, as confirmed by two-photon imaging. Targeted recordings reveal that parvalbumin-expressing (PV+) interneurons in mutant mice have reduced responses. PV-specific MeCP2 deletion alone recapitulates effects of global MeCP2 deletion on cortical circuits, including reduced pyramidal neuron responses and reduced response reliability and selectivity. Furthermore, MeCP2 mutant mice show reduced expression of the cation-chloride cotransporter KCC2 (K+/Cl- exporter) and a reduced KCC2/NKCC1 (Na+/K+/Cl- importer) ratio. Perforated patch recordings demonstrate that the reversal potential for GABA is more depolarized in mutant mice, but is restored by application of the NKCC1 inhibitor bumetanide. Treatment with recombinant human insulin-like growth factor-1 restores responses of PV+ and pyramidal neurons and increases KCC2 expression to normalize the KCC2/NKCC1 ratio. Thus, loss of MeCP2 in the brain alters both excitation and inhibition in brain circuits via multiple mechanisms. Loss of MeCP2 from a specific interneuron subtype contributes crucially to the cell-specific and circuit-wide deficits of RTT. The joint restoration of inhibition and excitation in cortical circuits is pivotal for functionally correcting the disorder.

Spatial Correlations in Natural Scenes Modulate Response Reliability in Mouse Visual Cortex.

Intrinsic neuronal variability significantly limits information encoding in the primary visual cortex (V1). Certain stimuli can suppress this intertrial variability to increase the reliability of neuronal responses. In particular, responses to natural scenes, which have broadband spatiotemporal statistics, are more reliable than responses to stimuli such as gratings. However, very little is known about which stimulus statistics modulate reliable coding and how this occurs at the neural ensemble level. Here, we sought to elucidate the role that spatial correlations in natural scenes play in reliable coding. We developed a novel noise-masking method to systematically alter spatial correlations in natural movies, without altering their edge structure. Using high-speed two-photon calcium imaging in vivo, we found that responses in mouse V1 were much less reliable at both the single neuron and population level when spatial correlations were removed from the image. This change in reliability was due to a reorganization of between-neuron correlations. Strongly correlated neurons formed ensembles that reliably and accurately encoded visual stimuli, whereas reducing spatial correlations reduced the activation of these ensembles, leading to an unreliable code. Together with an ensemble-specific normalization model, these results suggest that the coordinated activation of specific subsets of neurons underlies the reliable coding of natural scenes.

Clone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps.

Cognitive maps are mental representations of spatial and conceptual relationships in an environment, and are critical for flexible behavior. To form these abstract maps, the hippocampus has to learn to separate or merge aliased observations appropriately in different contexts in a manner that enables generalization and efficient planning. Here we propose a specific higher-order graph structure, clone-structured cognitive graph (CSCG), which forms clones of an observation for different contexts as a representation that addresses these problems. CSCGs can be learned efficiently using a probabilistic sequence model that is inherently robust to uncertainty. We show that CSCGs can explain a variety of cognitive map phenomena such as discovering spatial relations from aliased sensations, transitive inference between disjoint episodes, and formation of transferable schemas. Learning different clones for different contexts explains the emergence of splitter cells observed in maze navigation and event-specific responses in lap-running experiments. Moreover, learning and inference dynamics of CSCGs offer a coherent explanation for disparate place cell remapping phenomena. By lifting aliased observations into a hidden space, CSCGs reveal latent modularity useful for hierarchical abstraction and planning. Altogether, CSCG provides a simple unifying framework for understanding hippocampal function, and could be a pathway for forming relational abstractions in artificial intelligence.

Thalamic regulation of switching between cortical representations enables cognitive flexibility.

Interactions between the prefrontal cortex (PFC) and mediodorsal thalamus are critical for cognitive flexibility, yet the underlying computations are unknown. To investigate frontothalamic substrates of cognitive flexibility, we developed a behavioral task in which mice switched between different sets of learned cues that guided attention toward either visual or auditory targets. We found that PFC responses reflected both the individual cues and their meaning as task rules, indicating a hierarchical cue-to-rule transformation. Conversely, mediodorsal thalamus responses reflected the statistical regularity of cue presentation and were required for switching between such experimentally specified cueing contexts. A subset of these thalamic responses sustained context-relevant PFC representations, while another suppressed the context-irrelevant ones. Through modeling and experimental validation, we find that thalamic-mediated suppression may not only reduce PFC representational interference but could also preserve unused cortical traces for future use. Overall, our study provides a computational foundation for thalamic engagement in cognitive flexibility.