The limits of human visual short-term memory (VSTM) have been well documented, and recent neuroscientific studies suggest that VSTM performance is associated with activity in the posterior parietal cortex. Here we show that artificially elevating parietal activity via positively charged electric current through the skull can rapidly and effortlessly improve people's VSTM performance. This artificial improvement, however, comes with an interesting twist: it interacts with people's natural VSTM capability such that low performers who tend to remember less information benefitted from the stimulation, whereas high performers did not. This behavioral dichotomy is explained by event-related potentials around the parietal regions: low performers showed increased waveforms in N2pc and contralateral delay activity (CDA), which implies improvement in attention deployment and memory access in the current paradigm, respectively. Interestingly, these components are found during the presentation of the test array instead of the retention interval, from the parietal sites ipsilateral to the target location, thus suggesting that transcranial direct current stimulation (tDCS) was mainly improving one's ability to suppress no-change distractors located on the irrelevant side of the display during the comparison stage. The high performers, however, did not benefit from tDCS as they showed equally large waveforms in N2pc and CDA, or SPCN (sustained parietal contralateral negativity), before and after the stimulation such that electrical stimulation could not help any further, which also accurately accounts for our behavioral observations. Together, these results suggest that there is indeed a fixed upper limit in VSTM, but the low performers can benefit from neurostimulation to reach that maximum via enhanced comparison processes, and such behavioral improvement can be directly quantified and visualized by the magnitude of its associated electrophysiological waveforms.

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities.

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The interaction between goal-directed and stimulus-driven attentional control allows humans to rapidly reorient to relevant objects outside the focus of attention--a phenomenon termed contingent reorienting. Neuroimaging studies have observed activation of the ventral and dorsal attentional networks, but specific involvement of each network remains unclear. The present study aimed to determine whether both networks are critical to the processes of top-down contingent reorienting. To this end, we combined the contingent attentional capture paradigm with the use of transcranial magnetic stimulation (TMS) to interfere with temporoparietal junction (TPJ; ventral network) and frontal eye field (dorsal network) activity. The results showed that only right TPJ (rTPJ) TMS modulated contingent orienting. Furthermore, this modulation was highly dependent on visual fields: rTPJ TMS increased contingent capture in the left visual field and decreased the effect in the right visual field. These results demonstrate a critical involvement of the ventral network in attentional reorienting and reveal the spatial selectivity within such network.