Dissociating the causal role of left and right dorsal premotor cortices in planning and executing bimanual movements - A neuro-navigated rTMS study

BACKGROUND

The dorsal premotor cortex (PMd) is a key region in bimanual coordination. However, causal evidence linking PMd functionality during motor planning and execution to movement quality is lacking.

OBJECTIVE

We investigated how left (PMd_L) and right PMd (PMd_R) are causally involved in planning and executing bimanual movements, using short-train repetitive transcranial magnetic stimulation (rTMS). Additionally, we explored to what extent the observed rTMS-induced modulation of performance could be explained by rTMS-induced modulation of PMd-M1 interhemispheric interactions (IHI).

METHODS

Twenty healthy adults (mean age ± SD = 22.85 ± 3.73 years) participated in two sessions, in which either PMd_L or PMd_R was targeted with rTMS (10 Hz) in a pseudo-randomized design. PMd functionality was transiently modulated during the planning or execution of a complex bimanual task, whereby the participant was asked to track a moving dot by controlling two dials. The effect of rTMS on several performance measures was investigated. Concurrently, rTMS-induced modulation of PMd-M1 IHI was measured using a dual-coil paradigm, and associated with the rTMS-induced performance modulation.

RESULTS

rTMS over PMd_L during planning increased bilateral hand movement speed (p = 0.03), thereby improving movement accuracy (p = 0.02). In contrast, rTMS over PMd_R during both planning and execution induced deterioration of movement stability (p = 0.04). rTMS-induced modulation of PMd-M1 IHI during planning did not predict rTMS-induced performance modulation.

CONCLUSION

The current findings support the growing evidence on PMd_L dominance during motor planning, as PMd_L was crucially involved in planning the speed of each hand, subserving bimanual coordination accuracy. Moreover, the current results suggest that PMd_R fulfills a role in continuous adjustment processes of movement.

Perturbing the activity of the superior temporal gyrus during pain encoding prevents the exaggeration of pain memories: A virtual lesion study using single-pulse transcranial magnetic stimulation

BACKGROUND

Past studies have shown that pain memories are often inaccurate, a phenomenon known as mnemonic pain bias. Pain memories are thought to play an important role on how future pain is felt. Recent evidence from our laboratory suggests that individuals who exaggerate past pain display increased superior temporal gyrus (STG) activity during the encoding of experimental painful stimulations, suggesting that this brain structure plays an important role in pain memories.

OBJECTIVE

/hypothesis. To determine whether a virtual lesion paradigm, targeting the STG during pain encoding, can affect long-lasting pain memories. We hypothesized that interfering with the activity of the STG would attenuate mnemonic bias.

METHODS

Randomized double-blind study with two parallel groups. Participants received either sham (n = 21) or real (n = 21) transcranial magnetic stimulation (TMS - virtual lesion paradigm) over the STG during pain encoding (milliseconds after the administration of a painful stimuli). Pain intensity and unpleasantness were evaluated using a visual analog scale (VAS; 0 to 10) immediately after the painful event, and at recall, 2 months later. The mnemonic pain bias (calculated by subtracting the pain scores obtained at recall from the pain score obtained during encoding) was compared between the two groups for both pain intensity and unpleasantness.

RESULTS

Participants in both groups did not differ in terms of age and gender (real TMS = 27 years ± 9, 43% female; sham TMS = 25 years ± 4, 49% female; p > 0.64). The mnemonic bias related to pain intensity was similar in both groups (p = 0.83). However, the mnemonic bias related to pain unpleasantness was lower in the real TMS group (p = 0.04).

CONCLUSIONS

Our results provide the first evidence that the STG, is causally involved in the formation of biased memories of pain unpleasantness.

Does the regulation of local excitation-inhibition balance aid in recovery of functional connectivity? A computational account

Computational modeling of the spontaneous dynamics over the whole brain provides critical insight into the spatiotemporal organization of brain dynamics at multiple resolutions and their alteration to changes in brain structure (e.g. in diseased states, aging, across individuals). Recent experimental evidence further suggests that the adverse effect of lesions is visible on spontaneous dynamics characterized by changes in resting state functional connectivity and its graph theoretical properties (e.g. modularity). These changes originate from altered neural dynamics in individual brain areas that are otherwise poised towards a homeostatic equilibrium to maintain a stable excitatory and inhibitory activity. In this work, we employ a homeostatic inhibitory mechanism, balancing excitation and inhibition in the local brain areas of the entire cortex under neurological impairments like lesions to understand global functional recovery (across brain networks and individuals). Previous computational and empirical studies have demonstrated that the resting state functional connectivity varies primarily due to the location and specific topological characteristics of the lesion. We show that local homeostatic balance provides a functional recovery by re-establishing excitation-inhibition balance in all areas that are affected by lesion. We systematically compare the extent of recovery in the primary hub areas (e.g. default mode network (DMN), medial temporal lobe, medial prefrontal cortex) as well as other sensory areas like primary motor area, supplementary motor area, fronto-parietal and temporo-parietal networks. Our findings suggest that stability and richness similar to the normal brain dynamics at rest are achievable by re-establishment of balance.

The neurophysiology of language: Insights from non-invasive brain stimulation in the healthy human brain

With the advent of non-invasive brain stimulation (NIBS), a new decade in the study of language has started. NIBS allows for testing the functional relevance of language-related brain activation and enables the researcher to investigate how neural activation changes in response to focal perturbations. This review focuses on the application of NIBS in the healthy brain. First, some basic mechanisms will be introduced and the prerequisites for carrying out NIBS studies of language are addressed. The next section outlines how NIBS can be used to characterize the contribution of the stimulated area to a task. In this context, novel approaches such as multifocal transcranial magnetic stimulation and the condition-and-perturb approach are discussed. The third part addresses the combination of NIBS and neuroimaging in the study of plasticity. These approaches are particularly suited to investigate short-term reorganization in the healthy brain and may inform models of language recovery in post-stroke aphasia.

Modeling the effects of noninvasive transcranial brain stimulation at the biophysical, network, and cognitive level

Noninvasive transcranial brain stimulation (NTBS) is widely used to elucidate the contribution of different brain regions to various cognitive functions. Here we present three modeling approaches that are informed by functional or structural brain mapping or behavior profiling and discuss how these approaches advance the scientific potential of NTBS as an interventional tool in cognitive neuroscience. (i) Leveraging the anatomical information provided by structural imaging, the electric field distribution in the brain can be modeled and simulated. Biophysical modeling approaches generate testable predictions regarding the impact of interindividual variations in cortical anatomy on the injected electric fields or the influence of the orientation of current flow on the physiological stimulation effects. (ii) Functional brain mapping of the spatiotemporal neural dynamics during cognitive tasks can be used to construct causal network models. These models can identify spatiotemporal changes in effective connectivity during distinct cognitive states and allow for examining how effective connectivity is shaped by NTBS. (iii) Modeling the NTBS effects based on neuroimaging can be complemented by behavior-based cognitive models that exploit variations in task performance. For instance, NTBS-induced changes in response speed and accuracy can be explicitly modeled in a cognitive framework accounting for the speed-accuracy trade-off. This enables to dissociate between behavioral NTBS effects that emerge in the context of rapid automatic responses or in the context of slow deliberate responses. We argue that these complementary modeling approaches facilitate the use of NTBS as a means of dissecting the causal architecture of cognitive systems of the human brain.

Repetitive transcranial magnetic stimulation over left angular gyrus modulates the predictability gain in degraded speech comprehension

Increased neural activity in left angular gyrus (AG) accompanies successful comprehension of acoustically degraded but highly predictable sentences, as previous functional imaging studies have shown. However, it remains unclear whether the left AG is causally relevant for the comprehension of degraded speech. Here, we applied transient virtual lesions to either the left AG or superior parietal lobe (SPL, as a control area) with repetitive transcranial magnetic stimulation (rTMS) while healthy volunteers listened to and repeated sentences with high- versus low-predictable endings and different noise vocoding levels. We expected that rTMS of AG should selectively modulate the predictability gain (i.e., the comprehension benefit from sentences with high-predictable endings) at a medium degradation level. We found that rTMS of AG indeed reduced the predictability gain at a medium degradation level of 4-band noise vocoding (relative to control rTMS of SPL). In contrast, the behavioral perturbation induced by rTMS changed with increased signal quality. Hence, at 8-band noise vocoding, rTMS over AG versus SPL decreased the number of correctly repeated keywords for sentences with low-predictable endings. Together, these results show that the degree of the rTMS interference depended jointly on signal quality and predictability. Our results provide the first causal evidence that the left AG is a critical node for facilitating speech comprehension in challenging listening conditions.