Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex

Abstract

The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70–200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys’ behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators.

Prefrontal Markers and Cognitive Performance Are Dissociated during Progressive Dopamine Lesion

“…Perturbation or lesion of the MCC leads to behavioural impairment, at least over choice sequences [63–65], whilst neurophysiological signals in MCC clearly show trial-by-trial adjustment on the current task [12,13,66]. Reinforcement-learning theory of medial frontal performance monitoring signals hypothesizes a link with dopamine [10], and these signals are modified in some cases of diagnosed PD [40,43,44].…”

“…As a team, we have demonstrated the detailed neural correlates of both the feedback processing and behavioural adaptation elements of the task in both monkey and human subjects [12,13,18,23,66,79]. Specifically, the task induces delay activity in PFC comparable to that classically observed in working memory [18], induces responses to feedback that are modulated by control levels [12] and sensitive to dopamine [8], and explicitly requires control in that performance cannot be explained by simple reinforcement learning [13].…”

Cell assemblies at multiple time scales with arbitrary lag constellations

“…Numerous other statistical procedures for detecting assemblies or sequential patterns have been previously proposed (Abeles and Gerstein, 1988; Abeles and Gat, 2001, 2001b; Tetko and Villa, 2001a; Grün et al, 2002a, 2002b; Harris, 2005; Pipa et al, 2008; Sastry and Unnikrishnan, 2010; Staude et al, 2010a, 2010b; Humphries, 2011; Lopes-dos-Santos et al, 2011; Gansel and Singer, 2012; Gerstein et al, 2012; Shimazaki et al, 2012; Picado-Muiño et al, 2013; Torre et al, 2013, 2016a; Lopes-dos-Santos et al, 2013; Billeh et al, 2014; Logiaco et al, 2016), but most of these adhere to one or the other theoretical conceptualization of a cell assembly (cf. Figure 1A), or become (computationally) impractical for larger cell numbers or multiple lags, e.g.…”

Behavioral flexibility is associated with changes in structure and function distributed across a frontal cortical network in macaques

“…These two regions have been previously associated with reversal learning [14, 58]. ACC/MCC holds information about the value of choices other than the one that is being taken right now and translates such counterfactual choice values into actual behavioral change and exploration [30, 31, 59, 60]. DisRev may also be mediated by the acquisition of cognitive sets or task models, dependent on other interacting brain regions, representing the inter-relationships between the different choice-reward associations active in the task at different times [61, 62].…”