Highlights•Neural computation relies on compartmentalized dendrites to discern inputs•A method is described systematically derive the degree of compartmentalization•There are substantially fewer functional compartments than dendritic branches•Compartmentalization dynamic and can be tuned by synaptic inputsSummaryThe tree neurons plays an important role in information processing brain. While it thought that require independent subunits perform most their computations, still not understood how...

Dendrites shape information flow in neurons. Yet, there is little consensus on the level of spatial complexity at which they operate. Through carefully chosen parameter fits, solvable least-squares sense, we obtain accurate reduced compartmental models any complexity. We show that (back-propagating) action potentials, Ca2+ spikes, and N-methyl-D-aspartate spikes can all be reproduced with few compartments. also investigate whether afferent connectivity motifs admit simplification by ablating...

While sensory representations in the brain depend on context, it remains unclear how such modulations are implemented at biophysical level, and processing layers further hierarchy can extract useful features for each possible contextual state. Here, we demonstrate that dendritic N-Methyl-D-Aspartate spikes can, within physiological constraints, implement modulation of feedforward processing. Such neuron-specific exploit prior knowledge, encoded stable weights, to achieve transfer learning...

Mounting experimental evidence suggests the hypothesis that brain-state-specific neural mechanisms, supported by connectome shaped evolution, could play a crucial role in integrating past and contextual knowledge with current, incoming flow of (e.g., from sensory systems). These mechanisms would operate across multiple spatial temporal scales, necessitating dedicated support at levels individual neurons synapses. A notable feature within neocortex is structure large, deep pyramidal neurons,...

How sensory information is interpreted depends on context. Yet, how context shapes processing in the brain remains elusive. To investigate this question, we combined computational modeling and vivo functional imaging of cortical neurons mice during reversal learning a tactile discrimination task. During learning, layer 2/3 somatosensory enhanced their response to reward-predictive stimuli, explainable as gain amplification from apical dendrites. Reward-prediction errors were reduced...

We prove that when a class of partial differential equations, generalized from the cable equation, is defined on tree graphs and inputs are restricted to spatially discrete, well chosen set points, Green’s function (GF) formalism can be rewritten scale as [Formula: see text] with number n locations, contrary previously reported scaling. show linear scaling combined an expansion remaining kernels sums exponentials allow efficient simulations equations aforementioned class. furthermore...

Signal propagation in the dendrites of many neurons, including cortical pyramidal neurons sensory cortex, is characterized by strong attenuation toward soma. In contrast, using dual whole-cell recordings from apical dendrite and soma layer 5 (L5) anterior cingulate cortex (ACC) adult male mice we found good coupling, particularly slow subthreshold potentials like NMDA spikes or trains EPSPs to Only fastest ACC were reduced a similar degree as primary somatosensory revealing differential...

A fundamental function of cortical circuits is the integration information from different sources to form a reliable basis for behavior. While animals behave as if they optimally integrate according Bayesian probability theory, implementation required computations in biological substrate remains unclear. We propose novel, view on dynamics conductance-based neurons and synapses which suggests that are naturally equipped perform integration. In our approach apical dendrites represent prior...

Mounting experimental evidence suggests that brain-state-specific neural mechanisms, supported by connectomic architectures, play a crucial role in integrating past and contextual knowledge with the current, incoming flow of (e.g., from sensory systems). These mechanisms operate across multiple spatial temporal scales, necessitating dedicated support at levels individual neurons synapses. A notable feature within neocortex is structure large, deep pyramidal neurons, which exhibit distinctive...

Abstract While sensory representations in the brain depend on context, it remains unclear how such modulations are implemented at biophysical level, and processing layers further hierarchy can extract useful features for each possible contextual state. Here, we first demonstrate that thin dendritic branches well suited to implementing modulation of feedforward processing. Such neuron-specific exploit prior knowledge, encoded stable weights, achieve transfer learning across contexts. In a...

Abstract Dendrites shape information flow in neurons. Yet, there is little consensus on the level of spatial complexity at which they operate. We present a flexible and fast method to obtain simplified neuron models any complexity. Through carefully chosen parameter fits, solvable least squares sense, we optimal reduced compartmental models. show that (back-propagating) action potentials, calcium-spikes NMDA-spikes can all be reproduced with few compartments. also investigate whether...

Faithful reconstructions of cortical microcircuits allow the characterization synaptic pathways along with specific dendritic regions that they target on post-synaptic neurons [2]. But given this information, question remains how integrate or discriminate between distinct inputs impinging at spatially segregated locations their dendrites. Here, we investigated and under which circumstances targeting in dendrites can interact. We followed an analytical approach, starting a Volterra...

A fundamental function of cortical circuits is the integration information from different sources to form a reliable basis for behavior. While animals behave as if they optimally integrate according Bayesian probability theory, implementation required computations in biological substrate remains unclear. We propose novel, view on dynamics conductance-based neurons and synapses which suggests that are naturally equipped perform integration. In our approach apical dendrites represent prior...

We prove that when a class of partial differential equations, generalized from the cable equation, is defined on tree graphs, and inputs are restricted to spatially discrete, well chosen set points, Green's function (GF) formalism can be rewritten scale as $O(n)$ with number $n$ input locations, contrary previously reported $O(n^2)$ scaling. show linear scaling combined an expansion remaining kernels sums exponentials, allow efficient simulations equations aforementioned class. furthermore...

Event Abstract Back to A sparse reformulation of the Green's function formalism allows efficient simulations morphological neuron models Willem Wybo1*, Daniele Boccalini2, Benjamin Torben-Nielsen1, 3 and Marc-Oliver Gewaltig1 1 École polytechnique fédérale de Lausanne, Brain Mind Institute, Switzerland 2 Mathematics Institute for Geometry Applications, Okinawa Science Technology, Japan Neurons are spatially extended structures with an elaborate dendritic tree that integrates spatio-temporal...

Neurons are spatially extended structures that receive and process inputs on their dendrites. It is generally accepted neuronal computations arise from the active integration of synaptic along a dendrite between input location spike generation in axon initial segment. However, many application such as simulations brain networks, use point-neurons --neurons without morphological component-- computational units to keep conceptual complexity costs low. Inevitably, these applications thus omit...

Abstract The dendritic trees of neurons play an important role in the information processing brain. While it is tacitly assumed that dendrites require independent compartments to perform most their computational functions, still not understood how they compartmentalize into functional subunits. Here we show these subunits can be deduced from structural and electrical properties dendrites. We devised a mathematical formalism links arborization impedance-based tree-graph topology this reveals...