Large-scale dynamics of perceptual decision information across human cortex

Abstract

Perceptual decisions entail the accumulation of sensory evidence for a particular choice towards an action plan. An influential framework holds that sensory cortical areas encode the instantaneous sensory evidence and downstream, action-related regions accumulate this evidence. The large-scale distribution of this computation across the cerebral cortex has remained largely elusive. Here, we develop a regionally-specific magnetoencephalography decoding approach to exhaustively map the dynamics of stimulus- and choice-specific signals across the human cortical surface during a visual decision. Comparison with the evidence accumulation dynamics inferred from behavior disentangles stimulus-dependent and endogenous components of choice-predictive activity across the visual cortical hierarchy. We find such an endogenous component in early visual cortex (including V1), which is expressed in a low (<20 Hz) frequency band and tracks, with delay, the build-up of choice-predictive activity in (pre-) motor regions. Our results are consistent with choice- and frequency-specific cortical feedback signaling during decision formation.

Persistent Activity in Human Parietal Cortex Mediates Perceptual Choice Repetition Bias

“…In line with previous work (Pfurtscheller et al, 1996; Donner et al, 2009; Pape and Siegel, 2016; Murphy et al, 2021), the lateralization of low-frequency power (alpha- and beta-band) in areas implicated in action preparation and execution predicted the upcoming action: alpha-/beta-power was suppressed in the hemisphere contralateral vs. ipsilateral to the upcoming response hand, an effect that built up gradually during decision formation (Figure 3a). As in previous work (Wilming et al, 2020), this effect was present in multiple frontal and parietal cortical areas, such as the hand area of primary motor cortex (M1) and the parietal area IPS/PostCeS (Figure 4a, bottom). Enhancement of gamma lateralization around the button press (Figure 3a) was confined to IPS/PostCeS, PMd, and M1 (Figure 4a, top).…”

“…We analyzed known MEG signatures of visual motion processing and action planning (Siegel et al, 2006; Donner et al, 2009; Donner and Siegel, 2011; de Lange et al, 2013; Wilming et al, 2020; Murphy et al, 2021). During coherent motion viewing (reference and test), we observed occipital enhancement of high-frequency power (from about 30-100 Hz), accompanied by a suppression of low-frequency (< 30 Hz) power (Figure 1b).…”

“…To help constrain their functional interpretation, we focused on known signatures of sensory encoding and action preparation across cortical areas involved in decision-making. Specifically, we focused on band-limited signals from extrastriate visual field maps in occipital, temporal, and parietal cortex involved in visual motion processing (from areas MT+ and V3A/B to IPS2/3; (Tootell et al, 1997; Siegel et al, 2006; Wang et al, 2015)) and more anterior parietal and frontal areas involved in action preparation (IPS/PostCeS, PMd/v, and M1; (de Gee et al, 2017; Wilming et al, 2020; Murphy et al, 2021)).…”

Flexible categorization in perceptual decision making

“…These neural circuit mechanisms have been studied with biophysical attractor network models that can integrate stimulus evidence over relatively long time scales 19 , 20 . Attractor network models have been used, among other examples, to study the adjustment of speed-accuracy trade-off in a cortico-basal ganglia circuit 21 , learning dynamics of sensorimotor associations 22 , the generation of choice correlated sensory activity in hierarchical networks 23 – 25 , the role of the pulvino-cortical pathway in controlling the effective connectivity within and across cortical regions 26 or how trial history biases can emerge from the circuit dynamics 27 . In the typical regime in which the attractor network was originally used for perceptual categorization 19 , 28 , the impact of the stimulus on the decision decreases as the network evolves towards an attractor.…”

A confirmation bias in perceptual decision-making due to hierarchical approximate inference

“…Here, we focus on temporal biases, which range from over-weighting early evidence (a primacy effect) to over-weighting late evidence (a recency effect) ( Fig 1A ) even in situations when an equal weighting of evidence would be optimal. Despite seemingly comparable tasks, existing studies are surprisingly heterogeneous in the biases they find: some report primacy effects [ 7 – 9 ], some find that information is weighted equally over time [ 10 – 12 ], and some find recency effects [ 13 ] without a clear pattern emerging from the data.…”