One of the central questions in neuroscience is how particular tasks, or computations, are implemented by neural networks to generate behavior. The prevailing view has been that information processing in neural networks results primarily from the properties of synapses and the connectivity of neurons within the network, with the intrinsic excitability of single neurons playing a lesser role. As a consequence, the contribution of single neurons to computation in the brain has long been underestimated. Here we review recent work showing that neuronal dendrites exhibit a range of linear and nonlinear mechanisms that allow them to implement elementary computations. We discuss why these dendritic properties may be essential for the computations performed by the neuron and the network and provide theoretical and experimental examples to support this view.

Astrocytes respond to neuronal activity and were shown to be necessary for plasticity and memory. To test whether astrocytic activity is also sufficient to generate synaptic potentiation and enhance memory, we expressed the Gq-coupled receptor hM3Dq in CA1 astrocytes, allowing their activation by a designer drug. We discovered that astrocytic activation is not only necessary for synaptic plasticity, but also sufficient to induce NMDA-dependent de novo long-term potentiation in the hippocampus that persisted after astrocytic activation ceased. In vivo, astrocytic activation enhanced memory allocation; i.e., it increased neuronal activity in a task-specific way only when coupled with learning, but not in home-caged mice. Furthermore, astrocytic activation using either a chemogenetic or an optogenetic tool during acquisition resulted in memory recall enhancement on the following day. Conversely, directly increasing neuronal activity resulted in dramatic memory impairment. Our findings that astrocytes induce plasticity and enhance memory may have important clinical implications for cognitive augmentation treatments.

It is well known that neural activity exhibits variability, in the sense that identical sensory stimuli produce different responses, but it has been difficult to determine what this variability means. Is it noise, or does it carry important information – about, for example, the internal state of the organism? We address this issue from the bottom up, by asking whether small perturbations to activity in cortical networks are amplified. Based on in vivo whole-cell recordings in rat barrel cortex, we find that a perturbation consisting of a single extra spike in one neuron produces ~28 additional spikes in its postsynaptic targets, and we show, using simultaneous intra- and extra-cellular recordings, that a single spike produces a detectable increase in firing rate in the local network. Theoretical analysis indicates that this amplification leads to intrinsic, stimulus-independent variations in membrane potential on the order of ±2.2 - 4.5 mV – variations that are pure noise, and so carry no information at all. Therefore, for the brain to perform reliable computations, it must either use a rate code, or generate very large, fast depolarizing events, such as those proposed by the theory of synfire chains – yet in our in vivo recordings, we found that such events were very rare. Our findings are consistent with the idea that cortex is likely to use primarily a rate code.

The consolidation and retrieval of remote memories depend on the coordinated activity of the hippocampus and frontal cortices. However, the exact time at which these regions are recruited to support memory and the interactions between them are still debated. Astrocytes can sense and modify neuronal activity with great precision, but their role in cognitive function has not been extensively explored. To investigate the role of astrocytes in remote memory we expressed the Gi-coupled receptor hM4Di in CA1 astrocytes, allowing their manipulation by a designer drug. We discovered that astrocytic modulation during learning resulted in a specific impairment in remote, but not recent, memory recall, accompanied by decreased neuronal activity in the anterior cingulate cortex (ACC) during retrieval. We revealed a massive recruitment of ACC-projecting neurons in CA1 during memory acquisition, accompanied by activation of ACC neurons. Astrocytic Gi activation disrupted CA3 to CA1 communication in-vivo, and reduced the downstream response in the ACC. This same manipulation in behaving mice induced a projection-specific inhibition of ACCprojecting CA1 neurons during learning, consequently preventing the recruitment of the ACC. Our findings suggest that the foundation of remote memory is established in the ACC during acquisition, engaging a distinct process from the one supporting consolidation of recent memory. Furthermore, the mechanism underlying remote memory involves projection-specific functions of astrocytes in regulating neuronal activity.

Our understanding of the function of dendrites has been greatly enriched by an inspiring dialogue between theory and experiments. Rather than functionally ignoring dendrites, representing neurons as single summing points, we have realized that dendrites are electrically and chemically distributed nonlinear units and that this has important consequences for interpreting experimental data and for the role of neurons in information processing. Here, we examine the route to unraveling some of the enigmas of dendrites and highlight the main insights that have been gained. Future directions are discussed that will enable theory and models to keep shedding light on dendrites, where the most fundamental input-output adaptive processes take place.