Enhanced Dendritic Compartmentalization in Human Cortical Neurons.

The biophysical features of neurons shape information processing in the brain. Cortical neurons are larger in humans than in other species, but it is unclear how their size affects synaptic integration. Here, we perform direct electrical recordings from human dendrites and report enhanced electrical compartmentalization in layer 5 pyramidal neurons. Compared to rat dendrites, distal human dendrites provide limited excitation to the soma, even in the presence of dendritic spikes. Human somas also exhibit less bursting due to reduced recruitment of dendritic electrogenesis. Finally, we find that decreased ion channel densities result in higher input resistance and underlie the lower coupling of human dendrites. We conclude that the increased length of human neurons alters their input-output properties, which will impact cortical computation. VIDEO ABSTRACT.

Allometric rules for mammalian cortical layer 5 neuron biophysics.

The biophysical properties of neurons are the foundation for computation in the brain. Neuronal size is a key determinant of single neuron input-output features and varies substantially across species1-3. However, it is unknown whether different species adapt neuronal properties to conserve how single neurons process information4-7. Here we characterize layer 5 cortical pyramidal neurons across 10 mammalian species to identify the allometric relationships that govern how neuronal biophysics change with cell size. In 9 of the 10 species, we observe conserved rules that control the conductance of voltage-gated potassium and HCN channels. Species with larger neurons, and therefore a decreased surface-to-volume ratio, exhibit higher membrane ionic conductances. This relationship produces a conserved conductance per unit brain volume. These size-dependent rules result in large but predictable changes in somatic and dendritic integrative properties. Human neurons do not follow these allometric relationships, exhibiting much lower voltage-gated potassium and HCN conductances. Together, our results in layer 5 neurons identify conserved evolutionary principles for neuronal biophysics in mammals as well as notable features of the human cortex.

Ih interacts with somato-dendritic structure to determine frequency response to weak alternating electric field stimulation.

Transcranial current stimulation (tCS) modulates brain dynamics using weak electric fields. Given the pathological changes in brain network oscillations in neurological and psychiatric illnesses, using alternating electric field waveforms that engage rhythmic activity has been proposed as a targeted, network-level treatment approach. Previous studies have investigated the effects of electric fields at the neuronal level. However, the biophysical basis of the cellular response to electric fields has remained limited. Here, we characterized the frequency-dependent response of different compartments in a layer V pyramidal neuron to exogenous electric fields to dissect the relative contributions of voltage-gated ion channels and neuronal morphology. Hyperpolarization-activated cation current (Ih) in the distal dendrites was the primary ionic mechanism shaping the model's response to electric field stimulation and caused subthreshold resonance in the tuft at 20 ± 4 Hz. In contrast, subthreshold Ih-mediated resonance in response to local sinusoidal current injection was present in all model compartments at 11 ± 2 Hz. The frequencies of both resonance responses were modulated by Ih conductance density. We found that the difference in resonance frequency between the two stimulation types can be explained by the fact that exogenous electric fields simultaneously polarize the membrane potentials at the distal ends of the neuron (relative to field direction) in opposite directions. Our results highlight the role of Ih in shaping the cellular response to electric field stimulation and suggest that the common model of tCS as a weak somatic current injection fails to capture the cellular effects of electric field stimulation. NEW & NOTEWORTHY Modulation of cortical oscillation by brain stimulation serves as a tool to understand the causal role of network oscillations in behavior and is a potential treatment modality that engages impaired network oscillations in disorders of the central nervous system. To develop targeted stimulation paradigms, cellular-level effects must be understood. We demonstrate that hyperpolarization-activated cation current (Ih) and cell morphology cooperatively shape the response to applied alternating electric fields.

Coordinated head direction representations in mouse anterodorsal thalamic nucleus and retrosplenial cortex.

The sense of direction is critical for survival in changing environments and relies on flexibly integrating self-motion signals with external sensory cues. While the anatomical substrates involved in head direction (HD) coding are well known, the mechanisms by which visual information updates HD representations remain poorly understood. Retrosplenial cortex (RSC) plays a key role in forming coherent representations of space in mammals and it encodes a variety of navigational variables, including HD. Here, we use simultaneous two-area tetrode recording to show that RSC HD representation is nearly synchronous with that of the anterodorsal nucleus of thalamus (ADn), the obligatory thalamic relay of HD to cortex, during rotation of a prominent visual cue. Moreover, coordination of HD representations in the two regions is maintained during darkness. We further show that anatomical and functional connectivity are consistent with a strong feedforward drive of HD information from ADn to RSC, with anatomically restricted corticothalamic feedback. Together, our results indicate a concerted global HD reference update across cortex and thalamus.

Vectorized instructive signals in cortical dendrites during a brain-computer interface task.

Backpropagation of error is the most widely used learning algorithm in artificial neural networks, forming the backbone of modern machine learning and artificial intelligence1,2. Backpropagation provides a solution to the credit assignment problem by vectorizing an error signal tailored to individual neurons. Recent theoretical models have suggested that neural circuits could implement backpropagation-like learning by semi-independently processing feedforward and feedback information streams in separate dendritic compartments3-7. This presents a compelling, but untested, hypothesis for how cortical circuits could solve credit assignment in the brain. We designed a neurofeedback brain-computer interface (BCI) task with an experimenter-defined reward function to evaluate the key requirements for dendrites to implement backpropagation-like learning. We trained mice to modulate the activity of two spatially intermingled populations (4 or 5 neurons each) of layer 5 pyramidal neurons in the retrosplenial cortex to rotate a visual grating towards a target orientation while we recorded GCaMP activity from somas and corresponding distal apical dendrites. We observed that the relative magnitudes of somatic versus dendritic signals could be predicted using the activity of the surrounding network and contained information about task-related variables that could serve as instructive signals, including reward and error. The signs of these putative teaching signals both depended on the causal role of individual neurons in the task and predicted changes in overall activity over the course of learning. These results provide the first biological evidence of a backpropagation-like solution to the credit assignment problem in the brain.

Widespread and Highly Correlated Somato-dendritic Activity in Cortical Layer 5 Neurons.

Dendritic integration can expand the information-processing capabilities of neurons. However, the recruitment of active dendritic processing in vivo and its relationship to somatic activity remain poorly understood. Here, we use two-photon GCaMP6f imaging to simultaneously monitor dendritic and somatic compartments in the awake primary visual cortex. Activity in layer 5 pyramidal neuron somata and distal apical trunk dendrites shows surprisingly high functional correlation. This strong coupling persists across neural activity levels and is unchanged by visual stimuli and locomotion. Ex vivo combined somato-dendritic patch-clamp and GCaMP6f recordings indicate that dendritic signals specifically reflect local electrogenesis triggered by dendritic inputs or high-frequency bursts of somatic action potentials. In contrast to the view that dendrites are only sparsely recruited under highly specific conditions in vivo, our results provide evidence that active dendritic integration is a widespread and intrinsic feature of cortical computation.