Behavior Modulates Effective Connectivity between Cortex and Striatum

Abstract

It has been notoriously difficult to understand interactions in the basal ganglia because of multiple recurrent loops. Another complication is that activity there is strongly dependent on behavior, suggesting that directional interactions, or effective connections, can dynamically change. A simplifying approach would be to examine just the direct, monosynaptic projections from cortex to striatum and contrast this with the polysynaptic feedback connections from striatum to cortex. Previous work by others on effective connectivity in this pathway indicated that activity in cortex could be used to predict activity in striatum, but that striatal activity could not predict cortical activity. However, this work was conducted in anesthetized or seizing animals, making it impossible to know how free behavior might influence effective connectivity. To address this issue, we applied Granger causality to local field potential signals from cortex and striatum in freely behaving rats. Consistent with previous results, we found that effective connectivity was largely unidirectional, from cortex to striatum, during anesthetized and resting states. Interestingly, we found that effective connectivity became bidirectional during free behaviors. These results are the first to our knowledge to show that striatal influence on cortex can be as strong as cortical influence on striatum. In addition, these findings highlight how behavioral states can affect basal ganglia interactions. Finally, we suggest that this approach may be useful for studies of Parkinson's or Huntington's diseases, in which effective connectivity may change during movement.

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“…5C). Furthermore, coupling in the opposite direction (i.e., striatal unit activity and cortical LFP signal) showed a weaker response, demonstrating that interregional synchronization preferentially occurs from the cortex to striatum (Nakhnikian et al 2014), consistent with corticostriatal wiring. To further elucidate the spectral properties of this oscillatory coupling, we calculated the spike-LFP coherence in the resting state and found that the strongest frequency mode indeed occurred in the delta band (mean Ϯ SD: 2.8 Ϯ 0.5 Hz; Fig.…”

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“…However, cross-correlation is model dependent, unlike transfer entropy. Granger causality has been widely used to assess causal interactions between both continuous and discrete neural signals (Granger, 1969; Ding et al, 2006; Nakhnikian et al, 2014), though underlying assumptions about the analysis (e.g., Gaussian distributed data) must be thoroughly evaluated. Additionally, neural encoding is frequently assessed by applying statistical tests to neural signal observations under two conditions (e.g., stimulus on versus off or behavior A versus B).…”

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