Improving online and offline gain from repetitive practice using anodal tDCS at dorsal premotor cortex

Administering anodal transcranial direct current stimulation at the left dorsal premotor cortex (PMd) but not right PMd throughout the repetitive practice of three novel motor sequences resulted in improved offline performance usually only observed after interleaved practice. This gain only emerged following overnight sleep. These data are consistent with the proposed proprietary role of left PMd for motor sequence learning and the more recent claim that PMd is central to sleep-related consolidation of novel skill memory.

Encoding of vocal pitch in the dorsal premotor cortex during multi-talker speech recognition

In a recent study (Venezia et al., 2021), left dorsal premotor cortex (dPM) responded to vocal pitch during a degraded speech recognition task, but only when speech was rated as unintelligible. Crucially, vocal pitch was not relevant to the task. The present fMRI study (N = 25) tests the hypothesis that left dPM will respond to vocal pitch for increasingly intelligible speech in a multi-talker speech recognition task that emphasizes pitch for talker segregation. We applied spectrotemporal modulation distortion to independently modulate vocal pitch and phonetic content in two-talker (male/female) utterances across two conditions (Competing, Unison), only one of which required pitch-based segregation (Competing). A Bayesian hierarchical drift-diffusion model (HDDM) was used to predict speech recognition performance (3-AFC response times, accuracy coded) from the pattern of spectrotemporal distortion imposed on each trial. The model’s drift rate parameter, a d’-like measure of speech recognition performance, was strongly associated with vocal pitch for Competing but not Unison. In a second, Bayesian hierarchical brain-behavior model, we then regressed the HDDM’s posterior predictions of trial-wise drift rate against trial-wise fMRI activation amplitude. A significant positive association with overall drift rate, reflecting contributions from vocal pitch and/or phonetic content, was observed in left dPM in both conditions. A significant positive association with ‘pitch-restricted’ drift rate, reflecting only contributions from vocal pitch, was observed in left dPM but only in the Competing condition. These findings suggest that left dPM: (i) responds to vocal pitch; and (ii) can operate in an auditory-pitch mode and a phonetic-speech mode.

Non-linear dimensionality reduction on extracellular waveforms reveals cell type diversity in premotor cortex

Cortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Current in vivo methods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only a small amount of variation. Here, we develop a new method (WaveMAP) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We apply WaveMAP to extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. Using WaveMAP, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while revealing previously unknown diversity within these subtypes. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics. Such insights were weaker when using featurebased approaches. WaveMAP therefore provides a more nuanced understanding of the dynamics of cell types in cortical circuits.

Ageing and the ipsilateral M1 BOLD response: a connectivity study

Young people exhibit a negative BOLD response in ipsilateral primary motor cortex (M1) when making unilateral movements, such as button presses. This negative BOLD response becomes more positive as people age. Here we investigated why this occurs, in terms of the underlying effective connectivity and haemodynamics. We applied dynamic causal modelling (DCM) to task fMRI data from 635 participants aged 18-88 from the Cam-CAN dataset, who performed a cued button pressing task with their right hand. We found that connectivity from contralateral supplementary motor area (SMA) and dorsal premotor cortex (PMd) to ipsilateral M1 became more positive with age, explaining 44% of the variability across people in ipsilateral M1 responses. Neurovascular and haemodynamic parameters in the model were not able to explain the age-related shift to positive BOLD. Our results add to a body of evidence implicating neural, rather than vascular factors as the predominant cause of negative BOLD - while emphasising the importance of inter-hemispheric connectivity. This study provides a foundation for investigating the clinical and lifestyle factors that determine the sign and amplitude of the M1 BOLD response, which could serve as a proxy for neural and vascular health, via the underlying neurovascular mechanisms.

Disrupting short-term memory in premotor but not visual cortex affects serial dependence in visuomotor integration

Human behavior is biased by past experience. For example, when intercepting a moving target, the speed of previous targets will bias responses in future trials. Neural mechanisms underlying this so-called serial dependence are still under debate. Here, we tested the hypothesis that the previous trial leaves a neural trace in brain regions associated with encoding task-relevant information at visual and/or motor regions. We reasoned that injecting noise by means of transcranial magnetic stimulation (TMS) over premotor and visual areas would degrade such memory traces and hence reduce serial dependence. To test this hypothesis, we applied bursts of TMS pulses to right visual motion processing region hV5/MT+ and to left dorsal premotor cortex during inter-trial intervals of a coincident timing task performed by twenty healthy human participants (15 female). Without TMS, participants presented a bias towards the speed of the previous trial when intercepting moving targets. TMS over dorsal premotor cortex decreased serial dependence in comparison to the control Vertex stimulation, whereas TMS applied over hV5/MT+ did not. In addition, TMS seems to have specifically affected the memory trace that leads to serial dependence, as we show no evidence that participants’ behavior worsened after applying TMS. These results provide causal evidence that an implicit short-term memory mechanism in premotor cortex keeps information from one trial to the next, and that this information is blended with current trial information so that it biases behavior in a visuomotor integration task with moving objects.Significance StatementHuman perception and action are biased by the recent past. For example, the speed from previously experienced moving targets biases responses when hitting moving objects. The origin of such serial bias is still not fully understood, but a few components seem to be fundamental for its emergence: the brain needs to keep previous trial information in short-term memory and blend it with incoming information. Here, we present evidence that a premotor area has a potential role in storing previous trial information in implicit short-term memory in a visuomotor integration task, and that this information is responsible for causing biases on ongoing behavior. These results corroborate the perspective that areas associated with processing information of a stimulus or task also participate in maintaining that information in short-term memory even when this information is no longer relevant for current behavior.

Non-linear Dimensionality Reduction on Extracellular Waveforms Reveals Physiological, Functional, and Laminar Diversity in Premotor Cortex

Cortical circuits involved in decision-making are thought to contain a large number of cell types— each with different physiological, functional, and laminar distribution properties—that coordinate to produce behavior. Current in vivo methods rely on clustering of specified features, such as trough to peak duration of extracellular spikes, to identify putative cell types, but these can only capture a small amount of variation. Here, we develop a new method (WaveMAP) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We apply WaveMAP to extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. Using WaveMAP, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while also revealing undocumented diversity within these sub types. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics.SignificanceHow different cell types sculpt activity patterns in brain areas associated with decision-making is a fundamentally unresolved problem in neuroscience. In monkeys, and other species where transgenic access is not yet possible, identifying physiological types in vivo relies on only a few discrete user-specified features of extracellular waveforms to identify cell types. Here, we show that non-linear dimensionality reduction with graph clustering applied to the entire extracellular waveform can delineate many different putative cell types and does so in an interpretable manner. We show that this method reveals previously undocumented physiological, functional, and laminar diversity in the dorsal premotor cortex of monkeys, a key brain area implicated in decision-making.