Elucidating the role of retrosplenial cortex in history-based decision-making

Using past experience to inform future choice is fundamental to decision-making and behavior. Integrating experience by comparing choices and outcomes across time is a critical task, and requires a neural mechanism by which information may be assessed and accumulated. This is a widespread phenomenon in the brain, involving many cortical and subcortical structures. In this dissertation I show that one cortical area, the retrosplenial cortex (RSC), is particularly enriched in neurons that encode behaviorally-relevant history information, and is necessary for decision-making that relies on reward-history. RSC neurons exhibit a diversity of time-constants over which this history information is integrated, and I have found that the timescales encoded in RSC match the temporal characteristics of the behavior better than other cortical areas. I developed a novel behavioral model in which decision is reached as the weighted sum of multiple exponential integrators using the observed diversity of time-constants. Acutely inactivating RSC results in the attenuation of this combinatorial behavioral strategy, and a decreased reliance on reward-history. From these results, I propose a conceptual model where reward-history information is encoded in neurons with a simple update rule, but the time-constants are heterogenous and vary across the population. The combination of diverse temporal information produces a behavioral strategy which is sensitive to both recent experience and long-term trends, a feature observed as the hyperbolic discounting of past experience. In Chapter 1 I introduce the concepts of reinforcement learning theory relevant for this dissertation, and survey how reward-based value information is encoded in the brain. Chapter 2 identifies RSC as particularly important for the integration of past reward experience into actionable value information. Chapter 3 further examines and tests the role of RSC in integrating information across a diversity of timescales, and proposes a model of independent temporal integration in the brain that underlies the hyperbolic discounting of past experience. Chapter 4 discusses the properties of RSC that support the integration and maintenance of diverse information, and contextualizes the results in the broader decision-making contex

Area-Specificity and Plasticity of History-Dependent Value Coding During Learning

Decision making is often driven by the subjective value of available options, a value which is formed through experience. To support this fundamental behavior, the brain must encode and maintain the subjective value. To investigate the area specificity and plasticity of value coding, we trained mice in a value-based decision task and imaged neural activity in 6 cortical areas with cellular resolution. History- and value-related signals were widespread across areas, but their strength and temporal patterns differed. In expert mice, the retrosplenial cortex (RSC) uniquely encoded history- and value-related signals with persistent population activity patterns across trials. This unique encoding of RSC emerged during task learning with a strong increase in more distant history signals. Acute inactivation of RSC selectively impaired the reward-history-based behavioral strategy. Our results indicate that RSC flexibly changes its history coding and persistently encodes value-related signals to support adaptive behaviors

Exponential history integration with diverse temporal scales in retrosplenial cortex supports hyperbolic behavior.

Animals use past experience to guide future choices. The integration of experiences typically follows a hyperbolic, rather than exponential, decay pattern with a heavy tail for distant history. Hyperbolic integration affords sensitivity to both recent environmental dynamics and long-term trends. However, it is unknown how the brain implements hyperbolic integration. We found that mouse behavior in a foraging task showed hyperbolic decay of past experience, but the activity of cortical neurons showed exponential decay. We resolved this apparent mismatch by observing that cortical neurons encode history information with heterogeneous exponential time constants that vary across neurons. A model combining these diverse timescales recreated the heavy-tailed, hyperbolic history integration observed in behavior. In particular, the time constants of retrosplenial cortex (RSC) neurons best matched the behavior, and optogenetic inactivation of RSC uniquely reduced behavioral history dependence. These results indicate that behavior-relevant history information is maintained across multiple timescales in parallel and that RSC is a critical reservoir of information guiding decision-making

Optogenetics in Mice Performing a Visual Discrimination Task: Measurement and Suppression of Retinal Activation and the Resulting Behavioral Artifact.

Optogenetic techniques are used widely to perturb and interrogate neural circuits in behaving animals, but illumination can have additional effects, such as the activation of endogenous opsins in the retina. We found that illumination, delivered deep into the brain via an optical fiber, evoked a behavioral artifact in mice performing a visually guided discrimination task. Compared with blue (473 nm) and yellow (589 nm) illumination, red (640 nm) illumination evoked a greater behavioral artifact and more activity in the retina, the latter measured with electrical recordings. In the mouse, the sensitivity of retinal opsins declines steeply with wavelength across the visible spectrum, but propagation of light through brain tissue increases with wavelength. Our results suggest that poor retinal sensitivity to red light was overcome by relatively robust propagation of red light through brain tissue and stronger illumination of the retina by red than by blue or yellow light. Light adaptation of the retina, via an external source of illumination, suppressed retinal activation and the behavioral artifact without otherwise impacting behavioral performance. In summary, long wavelength optogenetic stimuli are particularly prone to evoke behavioral artifacts via activation of retinal opsins in the mouse, but light adaptation of the retina can provide a simple and effective mitigation of the artifact

Basal forebrain cell counts.

<p>Basal forebrain cell counts.</p

Membrane properties of cholinergic neurons.

<p>Membrane properties of cholinergic neurons.</p

Spike characteristics of cholinergic neurons in ChAT-Cre/Ai32(ChR2-YFP) and ChAT-Cre/Ai35(Arch-GFP) mice.

<p><b>(A)</b> Whole-cell recordings from a ChR2-YFP-labeled neuron in nucleus basalis in an acute slice, illustrating the spiking pattern (upper panel) and after-spike potentials (lower panel) when spikes were evoked by somatic current injections (upper panel 300 ms, 50 pA; lower panel 1 ms, 500 pA current). Dashed horizontal lines denote 0 mV. Resting membrane potentials were -50 mV and -51 mV for upper and lower recordings, respectively. <b>(B)</b> Mean ± SEM spiking frequency as a function of current injected at the somata of 10 cholinergic neurons from ChAT-Cre/Ai32(ChR2-YFP) mice. Grey line: mean spike rates for cholinergic neurons from wild-type mice, from Hedrick & Waters (2010). <b>(C)</b> Whole-cell recordings from an Arch-GFP-labeled neuron in nucleus basalis in an acute slice, illustrating the spiking pattern (upper panel) and after-spike potentials (lower panel) when spikes were evoked by somatic current injections (upper panel 300 ms, 150 pA; lower panel 1 ms, 2000 pA current). Dashed horizontal lines denote 0 mV. Resting membrane potentials were -53 mV and -52 mV for upper and lower recordings, respectively. <b>(D)</b> Mean ± SEM spiking frequency as a function of current injected at the somata of 9 cholinergic neurons from ChAT-Cre/Ai35(Arch-GFP) mice. Grey line: mean spike rates for cholinergic neurons from wild-type mice, from Hedrick & Waters (2010).</p

Cholinergic cell densities in basal forebrain.

<p>Cell densities of ChAT-positive neurons in basal forebrain from ChAT-Cre, ChAT-Cre/Ai32(ChR2-YFP), ChAT-Cre/Ai35(Arch-GFP) and C57BL/6J (WT) mice. Each bar represents mean ± SEM cell density from 3 mice.</p