The size and structure of the dendritic arbor play important roles in determining how synaptic inputs of neurons are converted to action potential output and how neurons are integrated in the surrounding neuronal network. Accordingly, neurons with aberrant morphology have been associated with neurological disorders. Dysmorphic, enlarged neurons are, for example, a hallmark of focal epileptogenic lesions like focal cortical dysplasia (FCDIIb) and gangliogliomas (GG). However, the regulatory mechanisms governing the development of dendrites are insufficiently understood. The evolutionary conserved Ste20/Hippo kinase pathway has been proposed to play an important role in regulating the formation and maintenance of dendritic architecture. A key element of this pathway, Ste20-like kinase (SLK), regulates cytoskeletal dynamics in non-neuronal cells and is strongly expressed throughout neuronal development. Nevertheless, its function in neurons is unknown. We found that during development of mouse cortical neurons, SLK has a surprisingly specific role for proper elaboration of higher, ≥ 3rd, order dendrites both in cultured neurons and living mice. Moreover, SLK is required to maintain excitation-inhibition balance. Specifically, SLK knockdown causes a selective loss of inhibitory synapses and functional inhibition after postnatal day 15, while excitatory neurotransmission is unaffected. This mechanism may be relevant for human disease, as dysmorphic neurons within human cortical malformations exhibit significant loss of SLK expression. To uncover the signaling cascades underlying the action of SLK, we combined phosphoproteomics, protein interaction screens and single cell RNA seq. Overall, our data identifies SLK as a key regulator of both dendritic complexity during development and of inhibitory synapse maintenance.

Coordination between excitatory and inhibitory synapses (providing positive and negative signals respectively) is required to ensure proper information processing in the brain. Many brain disorders, especially neurodevelopental disorders, are rooted in a specific disturbance of this coordination. In my research group we use a combination of two-photon microscopy and electrophisiology to examine how inhibitory synapses are fromed and how this formation is coordinated with nearby excitatroy synapses.

Memory consolidation is the process by which recent experiences are assimilated into long-term memory. In animals, this process requires the offline replay of sequences observed during online exploration in the hippocampus. Recent experimental work has found that salient but task-irrelevant stimuli are systematically excluded from these replay epochs, suggesting that replay samples from an abstracted model of the world, rather than verbatim previous experiences. We find that this phenomenon can be explained parsimoniously and biologically plausibly by a Hebbian spike time-dependent plasticity rule at inhibitory synapses. Using spiking networks at three levels of abstraction–leaky integrate-and-fire, biophysically detailed, and abstract binary–we show that this rule enables efficient inference of a model of the structure of the world. While plasticity has previously mainly been studied at excitatory synapses, we find that plasticity at excitatory synapses alone is insufficient to accomplish this type of structural learning. We present theoretical results in a simplified model showing that in the presence of Hebbian excitatory and inhibitory plasticity, the replayed sequences form a statistical estimator of a latent sequence, which converges asymptotically to the ground truth. Our work outlines a direct link between the synaptic and cognitive levels of memory consolidation, and highlights a potential conceptually distinct role for inhibition in computing with SNNs.

Behavioral experience shapes neural circuits, adding and subtracting connections between neurons that will ultimately control sensation and perception. We are using natural sensory experience to uncover basic principles of information processing in the cerebral cortex, with a focus on how sensory learning can selectively alter synaptic strength. I will discuss recent findings that differentiate reinforcement learning from sensory experience, showing rapid and selective plasticity of thalamic and inhibitory synapses within primary sensory cortex.

In many butterflies, the ancestral trichromatic insect colour vision, based on UV-, blue- and green-sensitive photoreceptors, is extended with red-sensitive cells. Physiological evidence for red receptors has been missing in nymphalid butterflies, although some species can discriminate red hues well. In eight species from genera Archaeoprepona, Argynnis, Charaxes, Danaus, Melitaea, Morpho, Heliconius and Speyeria, we found a novel class of green-sensitive photoreceptors that have hyperpolarizing responses to stimulation with red light. These green-positive, red-negative (G+R–) cells are allocated to positions R1/2, normally occupied by UV and blue-sensitive cells. Spectral sensitivity, polarization sensitivity and temporal dynamics suggest that the red opponent units (R–) are the basal photoreceptors R9, interacting with R1/2 in the same ommatidia via direct inhibitory synapses. We found the G+R– cells exclusively in butterflies with red-shining ommatidia, which contain longitudinal screening pigments. The implementation of the red colour channel with R9 is different from pierid and papilionid butterflies, where cells R5–8 are the red receptors. The nymphalid red-green opponent channel and the potential for tetrachromacy seem to have been switched on several times during evolution, balancing between the cost of neural processing and the value of extended colour information.

The CA1 pyramidal neurons are embedded in an intricate local circuitry that contains a variety of interneurons. The roles these interneurons play in the regulation of the excitatory synaptic plasticity remains largely understudied. Recent experiments showed that repeated cholinergic activation of 𝛼7 nACh receptors expressed in oriens-lacunosum-moleculare (OLM𝛼2) interneurons could induce LTP in SC-CA1 synapses. We used a biophysically realistic computational model to examine mechanistically how cholinergic activation of OLMa2 interneurons increases SC to CA1 transmission. Our results suggest that, when properly timed, activation of OLMa2 interneurons cancels the feedforward inhibition onto CA1 pyramidal cells by inhibiting fast-spiking interneurons that synapse on the same dendritic compartment as the SC, i.e., by disinhibiting the pyramidal cell dendritic compartment. Our work further describes the pairing of disinhibition with SC stimulation as a general mechanism for the induction of synaptic plasticity. We found that locally-reduced GABA release (disinhibition) paired with SC stimulation could lead to increased NMDAR activation and intracellular calcium concentration sufficient to upregulate AMPAR permeability and potentiate the excitatory synapse. Our work suggests that inhibitory synapses critically modulate excitatory neurotransmission and induction of plasticity at excitatory synapses. Our work also shows how cholinergic action on OLM interneurons, a mechanism whose disruption is associated with memory impairment, can down-regulate the GABAergic signaling into CA1 pyramidal cells and facilitate potentiation of the SC-CA1 synapse.

Biological neural networks can represent information in the collective action potential discharge of neurons, and store that information amongst the synaptic connections between the neurons that both comprise the network and govern its function. The strength and organization of synaptic connections adjust during learning, but many cognitive neural systems are multifunctional, making it unclear how continuous activity alternates between the transient and discrete cognitive functions like encoding current information and recollecting past information, without changing the connections amongst the neurons. This lecture will first summarize our investigations of the molecular and biochemical mechanisms that change synaptic function to persistently store spatial memory in the rodent hippocampus. I will then report on how entorhinal cortex-hippocampus circuit function changes during cognitive training that creates memory, as well as learning to learn in mice. I will then describe how the hippocampus system operates like a competitive winner-take-all network, that, based on the dominance of its current inputs, self organizes into either the encoding or recollection information processing modes. We find no evidence that distinct cells are dedicated to those two distinct functions, rather activation of the hippocampus information processing mode is controlled by a subset of dentate spike events within the network of learning-modified, entorhinal-hippocampus excitatory and inhibitory synapses.

Biological neural networks can represent information in the collective action potential discharge of neurons, and store that information amongst the synaptic connections between the neurons that both comprise the network and govern its function. The strength and organization of synaptic connections adjust during learning, but many cognitive neural systems are multifunctional, making it unclear how continuous activity alternates between the transient and discrete cognitive functions like encoding current information and recollecting past information, without changing the connections amongst the neurons. This lecture will first summarize our investigations of the molecular and biochemical mechanisms that change synaptic function to persistently store spatial memory in the rodent hippocampus. I will then report on how entorhinal cortex-hippocampus circuit function changes during cognitive training that creates memory, as well as learning to learn in mice. I will then describe how the hippocampus system operates like a competitive winner-take-all network, that, based on the dominance of its current inputs, self organizes into either the encoding or recollection information processing modes. We find no evidence that distinct cells are dedicated to those two distinct functions, rather activation of the hippocampus information processing mode is controlled by a subset of dentate spike events within the network of learning-modified, entorhinal-hippocampus excitatory and inhibitory synapses.

How does a circuit of neurons process sensory information? And how are transformations of neural signals altered by changes in synaptic strength? We investigate these questions in the context of the visual system and the lateral line of fish. A distinguishing feature of our approach is the imaging of activity across populations of synapses – the fundamental elements of signal transfer within all brain circuits. A guiding hypothesis is that the plasticity of neurotransmission plays a major part in controlling the input-output relation of sensory circuits, regulating the tuning and sensitivity of neurons to allow adaptation or sensitization to particular features of the input. Sensory systems continuously adjust their input-output relation according to the recent history of the stimulus. A common alteration is a decrease in the gain of the response to a constant feature of the input, termed adaptation. For instance, in the retina, many of the ganglion cells (RGCs) providing the output produce their strongest responses just after the temporal contrast of the stimulus increases, but the response declines if this input is maintained. The advantage of adaptation is that it prevents saturation of the response to strong stimuli and allows for continued signaling of future increases in stimulus strength. But adaptation comes at a cost: a reduced sensitivity to a future decrease in stimulus strength. The retina compensates for this loss of information through an intriguing strategy: while some RGCs adapt following a strong stimulus, a second population gradually becomes sensitized. We found that the underlying circuit mechanisms involve two opposing forms of synaptic plasticity in bipolar cells: synaptic depression causes adaptation and facilitation causes sensitization. Facilitation is in turn caused by depression in inhibitory synapses providing negative feedback. These opposing forms of plasticity can cause simultaneous increases and decreases in contrast-sensitivity of different RGCs, which suggests a general framework for understanding the function of sensory circuits: plasticity of both excitatory and inhibitory synapses control dynamic changes in tuning and gain.

The remarkable cognitive abilities characterizing humans has been linked to unique patterns of connectivity characterizing the neocortex. Comparative studies have shown that human cortical pyramidal neurons (PN) receive a significant increase of synaptic inputs when compared to other mammals, including non-human primates and rodents, but how this may relate to changes in cortical connectivity and function remained largely unknown. We previously identified a human-specific gene duplication (HSGD), SRGAP2C, that, when induced in mouse cortical PNs drives human-specific features of synaptic development, including a correlated increase in excitatory (E) and inhibitory (I) synapse density through inhibition of the ancestral SRGAP2A protein (Charrier et al. 2012; Fossatti et al. 2016; Schmidt et al. 2019). However, the origin and nature of this increased connectivity and its impact on cortical circuit function was unknown. I will present new results exploring these questions (see Schmidt et al. (2020) https://www.biorxiv.org/content/10.1101/852970v1). Using a combination of transgenic approaches and quantitative monosynaptic tracing, we discovered that humanization of SRGAP2C expression in the mouse cortex leads to a specific increase in local and long-range cortico-cortical inputs received by layer 2/3 cortical PNs. Moreover, using in vivo two-photon imaging in the barrel cortex of awake mice, we show that humanization of SRGAP2C expression increases the reliability and selectivity of sensory- evoked responses in layer 2/3 PNs. We also found that mice humanized for SRGAP2C in all cortical pyramidal neurons and throughout development are characterized by improved behavioural performance in a novel whisker-based sensory discrimination task compared to control wild-type mice. Our results suggest that the emergence of SRGAP2C during human evolution underlie a new substrate for human brain evolution whereby it led to increased local and long-range cortico-cortical connectivity and improved reliability of sensory-evoked cortical coding. References cited Charrier C.*, Joshi K. *, Coutinho-Budd J., Kim, J-E., Lambert N., de Marchena, J., Jin W-L., Vanderhaeghen P., Ghosh A., Sassa T, and Polleux F. (2012) Inhibition of SRGAP2 function by its human-specific paralogs induces neoteny of spine maturation. Cell 149:923-935. * Co-first authors. Fossati M, Pizzarelli R, Schmidt ER, Kupferman JV, Stroebel D, Polleux F*, Charrier C*. (2016) SRGAP2 and Its Human-Specific Paralog Co-Regulate the Development of Excitatory and Inhibitory Synapses. Neuron. 91(2):356-69. * Co-senior corresponding authors. Schmidt E.R.E., Kupferman J.V., Stackmann M., Polleux F. (2019) The human-specific paralogs SRGAP2 and SRGAP2C differentially modulate SRGAP2A-dependent synaptic development. Scientific Rep. 9(1):18692. Schmidt E.R.E, Zhao H.T., Hillman E.M.C., Polleux F. (2020) Humanization of SRGAP2C expression increases cortico-cortical connectivity and reliability of sensory-evoked responses in mouse brain. Submitted. See also: https://www.biorxiv.org/content/10.1101/852970v1