Topic: pyramidal neurons

Pyramidal neurons have apical dendrites that are both physically and electrically segregated from their cell bodies. In sensory cortex, these apical dendrites receive primarily top-down signals from associative and motor regions, while the cell bodies and nearby dendrites of these same pyramidal neurons are mostly targeted by bottom-up or locally recurrent inputs from the sensory periphery. Due to these differences, a number of theories in computational neuroscience postulate a unique role for apical dendrites in shaping sensory processing and plasticity in the face of new or surprising stimul

A central problem in biological learning is how information about the outcome of a decision or behavior can be used to reliably guide learning across distributed neural circuits while obeying biological constraints. This “credit assignment” problem is commonly solved in artificial neural networks through supervised gradient descent and the backpropagation algorithm. In contrast, biological learning is typically modelled using unsupervised Hebbian learning rules. While these rules only use local information to update synaptic weights, and are sometimes combined with weight constraints to reflec

GABAergic interneurons are chiefly responsible for controlling the activity of local circuits in the cortex. Chandelier cells (ChCs) are a type of GABAergic interneuron that control the output of hundreds of neighbouring pyramidal cells through axo-axonic synapses which target the axon initial segment (AIS). Despite their importance in modulating circuit activity, our knowledge of the development and function of axo-axonic synapses remains elusive. We have investigated the emergence and plasticity of axo-axonic synapses in layer 2/3 of the somatosensory cortex (S1) and found that ChCs follow w

Understanding how cortical circuits generate complex behavior requires investigating the cell types that comprise them. Here, much effort has been focused on inhibitory neuron types but the functional roles of distinct classes of excitatory pyramidal neurons (PyNs) are less well un-derstood. We, therefore, used widefield imaging to measure the cortex-wide activity of distinct PyN types and investigated their functional role in mice that performed an auditory decision-making task. We used two mouse lines, expressing the calcium indicator GCaMP6s in two major PyN types: FezF2 for pyramidal-tract

The gradual accumulation of hyperphosphorylated forms of the Tau protein (pTau) in the human brain correlate with cognitive dysfunction and neurodegeneration. I will present our recent findings on the consequences of human pTau aggregation in the hippocampal formation of a mouse tauopathy model. We show that pTau preferentially accumulates in deep-layer pyramidal neurons, leading to their neurodegeneration. In aged but not younger mice, pTau spreads to oligodendrocytes. During ‘goal-directed’ navigation, we detect fewer high-firing pyramidal cells, but coupling to network oscillations is maint

Cortical circuits process information by rich recurrent interactions between excitatory neurons and inhibitory interneurons. One of the prime functions of interneurons is to stabilize the circuit by feedback inhibition, but the level of specificity on which inhibitory feedback operates is not fully resolved. We hypothesized that inhibitory circuits could enable separate feedback control loops for different synaptic input streams, by means of specific feedback inhibition to different neuronal compartments. To investigate this hypothesis, we adopted an optimization approach. Leveraging recent ad

Predictive learning hypotheses posit that the neocortex learns a hierarchical model of the structure of features in the environment. Under these hypotheses, expected or predictable features are differentiated from unexpected ones by comparing bottom-up and top-down streams of data, with unexpected features then driving changes in the representation of incoming stimuli. This is supported by numerous studies in early sensory cortices showing that pyramidal neurons respond particularly strongly to unexpected stimulus events. However, it remains unknown how their responses govern subsequent change

Sensory experience and perceptual learning changes receptive field properties of cortical pyramidal neurons possibly mediated by long-term potentiation (LTP) of synapses. We have previously shown in the mouse somatosensory cortex (S1) that sensory-driven LTP in layer (L) 2/3 pyramidal neurons is dependent on higher order thalamic feedback from the posteromedial nucleus (POm), which is thought to convey contextual information from various cortical regions integrated with sensory input. We have followed up on this work by dissecting the cortical microcircuitry that underlies this form of LTP

Arguably one of the biggest mysteries in neuroscience is how the brain stores long-term memories. The major challenge for investigating the neural circuit underlying memory formation in the neocortex is the distributed nature of the resulting memory trace throughout the cortex. Here, we used a new behavioral paradigm that enabled us to generate memory traces in a specific cortical location and to specifically examine the mechanisms of memory formation in that region. We found that medial-temporal inputs arrive in neocortical layer 1 where the apical dendrites of cortical pyramidal neurons pre

Higher-order thalamic nuclei have extensive connections with various cortical areas. Yet their functionals roles remain not well understood. In our recent studies, using optogenetic and chemogenetic tools we manipulated the activity of a higher-order thalamic nucleus, the lateral posterior nucleus (LP, analogous to the primate pulvinar nucleus) and its projections and examined the effects on sensory discrimination and information processing functions in the cortex. We found an overall suppressive effect on layer 2/3 pyramidal neurons in the cortex, resulting in enhancements of sensory featu

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 devel

The mammalian neocortex possesses the remarkable ability to translate complex sensory inputs into abstract representations through the coordinated activity of large neuronal ensembles across the sensory hierarchy. Theoretical works have proposed a variety of algorithms to coordinate learning across this hierarchy, including approximations of backpropagation of error as well as target-based methods such as predictive coding or control methods. In order to test the biological validity of these algorithms, we analyze the learning principles of the cortex, starting at the level of the synapse and

Artificial recurrent neural networks (RNNs) are difficult to train due to their tendency towards instability, and common training algorithms that tame such networks are not biologically plausible, i.e., back-propagation through time (BPTT). Node perturbation learning in combination with local Hebbian weight updates has been shown to approximate BPTT [1] and, thus, could achieve similar performance while being biologically plausible. However, where these perturbations could arise from and how they are utilized within neurons remains obscure. For years, the neuroscientific community has known ab