Surprisingly, past work has shown that neuroprosthetic skills rely on similar neural substrates as natural motor learning (Green and Kalaska, 2011) and therefore have similar computational

requirements for rapid and flexible information transfer. Importantly, BMI tasks offer the unique advantage that researchers can define which neuronal ensembles are directly relevant for behavioral output, therefore allowing for an investigation of functional specificity within local populations. Recent theories have proposed that alterations in the pattern of large-scale synchronous activity could serve as the substrate for the flexible neuronal associations necessary to coordinate network activity for performance of both natural and neuroprosthetic behaviors click here (Womelsdorf et al., 2007 and Canolty et al., 2010). Oscillatory local field potential (LFP) activity reflects rhythmic current flow across cell membranes in local ensembles and is hypothesized to alter the excitability of cell groups across different spatiotemporal selleck chemicals llc scales (Buzsáki and Draguhn, 2004, Lakatos et al., 2005 and Fröhlich and McCormick, 2010). Therefore, precise temporal control in neural networks could enhance the efficiency of information transfer in specific populations (Wang et al., 2010 and Tiesinga et al., 2001). It could also serve as a mechanism for synaptic gain control (Zeitler et al., 2008) and influence spike-timing-dependent

plasticity (Huerta and Lisman, 1993 and Harris et al., 2003), as spikes arriving at

excitability peaks will have enhanced efficacy relative to poorly timed spikes. Temporally coordinated activity in ensembles of neurons has been implicated in processes as diverse as perception (Rodriguez et al., 1999), expectation (von Stein et al., 2000), decision making (Pesaran et al., 2008), coordination (Dean et al., 2012), memory (Pesaran et al., 2002 and Siegel et al., 2009), spatial cognition (Colgin et al., 2009), reward processing (van der Meer and Redish, 2011), and attentional shifting (Bollimunta et al., 2011, Lakatos et al., 2008 and Fries et al., 2008). In some cases, this synchrony manifests as spiking in one region, becoming highly coordinated with LFP activity in a separate region (Pesaran et al., 2008). Importantly, many tasks evoke changes in the temporal pattern science of spiking without concomitant changes in firing rate, suggesting that synchrony could serve as an additional information channel in neural circuits (Riehle et al., 1997). Alterations in synchrony and LFP dynamics have also been implicated in pathological states such as epilepsy (Bragin et al., 2010) and Parkinson’s disease (Costa et al., 2006), highlighting their importance for normal brain functioning. Despite increasing evidence that changes in synchronous LFP activity are related to changes in behavior during learning (DeCoteau et al.