“Just as the Indian was branded a savage beast to justify his exploitation, so those who have sought social guerrillas, or terrorists, or drug dealers, or whatever the current term of art may be.” (Piero Gleijeses, as cited by Noam Chomsky)
Neural top–down control of physiology concerns the direct regulation by the brain of emotional and physiological functions. Cellular functions include the immune system’s production of T-lymphocytes and antibodies, and nonimmune related homeostatic functions such as liver gluconeogenesis, sodium reabsorption, osmoregulation, and brown adipose tissue nonshivering thermogenesis.More at Wikipedia
Chiesa, A., Serretti, A., & Jakobsen, J. C.. (2013). Mindfulness: Top-down or bottom-up emotion regulation strategy?. Clinical Psychology Review
McRae, K., Misra, S., Prasad, A. K., Pereira, S. C., & Gross, J. J.. (2012). Bottom-up and top-down emotion generation: Implications for emotion regulation. Social Cognitive and Affective Neuroscience
“Emotion regulation plays a crucial role in adaptive functioning and mounting evidence suggests that some emotion regulation strategies are often more effective than others. however, little attention has been paid to the different ways emotions can be generated: from the ‘bottom-up’ (in response to inherently emotional perceptual properties of the stimulus) or ‘top-down’ (in response to cognitive evaluations). based on a process priming principle, we hypothesized that mode of emotion generation would interact with subsequent emotion regulation. specifically, we predicted that top-down emotions would be more successfully regulated by a top-down regulation strategy than bottom-up emotions. to test this hypothesis, we induced bottom-up and top-down emotions, and asked participants to decrease the negative impact of these emotions using cognitive reappraisal. we observed the predicted interaction between generation and regulation in two measures of emotional responding. as measured by self-reported affect, cognitive reappraisal was more successful on top-down generated emotions than bottom-up generated emotions. neurally, reappraisal of bottom-up generated emotions resulted in a paradoxical increase of amygdala activity. this interaction between mode of emotion generation and subsequent regulation should be taken into account when comparing of the efficacy of different types of emotion regulation, as well as when reappraisal is used to treat different types of clinical disorders.”
Terhune, D. B., Cleeremans, A., Raz, A., & Lynn, S. J.. (2017). Hypnosis and top-down regulation of consciousness. Neuroscience and Biobehavioral Reviews
“Hypnosis is a unique form of top-down regulation in which verbal suggestions are capable of eliciting pronounced changes in a multitude of psychological phenomena. hypnotic suggestion has been widely used both as a technique for studying basic science questions regarding human consciousness but also as a method for targeting a range of symptoms within a therapeutic context. here we provide a synthesis of current knowledge regarding the characteristics and neurocognitive mechanisms of hypnosis. we review evidence from cognitive neuroscience, experimental psychopathology, and clinical psychology regarding the utility of hypnosis as an experimental method for modulating consciousness, as a model for studying healthy and pathological cognition, and as a therapeutic vehicle. we also highlight the relations between hypnosis and other psychological phenomena, including the broader domain of suggestion and suggestibility, and conclude by identifying the most salient challenges confronting the nascent cognitive neuroscience of hypnosis and outlining future directions for research on hypnosis and suggestion.”
Zelazo, P. D., & Carlson, S. M.. (2012). Hot and Cool Executive Function in Childhood and Adolescence: Development and Plasticity. Child Development Perspectives
“Executive function (ef), which refers to the more deliberate, top-down neurocognitive processes involved in self-regulation, develops most rapidly during the preschool years, together with the growth of neural networks involving prefrontal cortex but continues to develop well into adulthood. both ef and the neural systems supporting ef vary as a function of motivational significance, and this article discusses the distinction between the top-down processes that operate in motivationally and emotionally significant situations (‘hot ef’) and the top-down processes that operate is more affectively neutral contexts (‘cool ef’). emerging evidence indicates that both hot and cool ef are surprisingly malleable, with implications for intervention and prevention.”
Johnstone, T., van Reekum, C. M., Urry, H. L., Kalin, N. H., & Davidson, R. J.. (2007). Failure to Regulate: Counterproductive Recruitment of Top-Down Prefrontal-Subcortical Circuitry in Major Depression. Journal of Neuroscience
“Although depressed mood is a normal occurrence in response to adversity in all individuals, what distinguishes those who are vulnerable to major depressive disorder (mdd) is their inability to effectively regulate negative mood when it arises. investigating the neural underpinnings of adaptive emotion regulation and the extent to which such processes are compromised in mdd may be helpful in understanding the pathophysiology of depression. we report results from a functional magnetic resonance imaging study demonstrating left-lateralized activation in the prefrontal cortex (pfc) when downregulating negative affect in nondepressed individuals, whereas depressed individuals showed bilateral pfc activation. furthermore, during an effortful affective reappraisal task, nondepressed individuals showed an inverse relationship between activation in left ventrolateral pfc and the amygdala that is mediated by the ventromedial pfc (vmpfc). no such relationship was found for depressed individuals, who instead show a positive association between vmpfc and amygdala. pupil dilation data suggest that those depressed patients who expend more effort to reappraise negative stimuli are characterized by accentuated activation in the amygdala, insula, and thalamus, whereas nondepressed individuals exhibit the opposite pattern. these findings indicate that a key feature underlying the pathophysiology of major depression is the counterproductive engagement of right prefrontal cortex and the lack of engagement of left lateral-ventromedial prefrontal circuitry important for the downregulation of amygdala responses to negative stimuli.”
Heatherton, T. F., & Wagner, D. D.. (2011). Cognitive neuroscience of self-regulation failure. Trends in Cognitive Sciences
Holzman, J. B., & Bridgett, D. J.. (2017). Heart rate variability indices as bio-markers of top-downself-regulatory mechanisms: A meta-analytic review. Neuroscience and Biobehavioral Reviews
“Theoretical perspectives posit that heart-rate variability (hrv) reflects self-regulatory capacity and therefore can be employed as a bio-marker of top-downself-regulation (the ability to regulate behavioral, cognitive, and emotional processes). however, existing findings of relations between self-regulation and hrv indices are mixed. to clarify the nature of such relations, we conducted a meta-analysis of 123 studies (n = 14,347) reporting relations between hrv indices and aspects of top-downself-regulation (e.g., executive functioning, emotion regulation, effortful control). a significant, albeit small, effect was observed (r = 0.09) such that greater hrv was related to better top-downself-regulation. differences in relations were negligible across aspects of self-regulation, self-regulation measurement methods, hrv computational techniques, at-risk compared with healthy samples, and the context of hrv measurement. stronger relations were observed in older relative to younger samples and in published compared to unpublished studies. these findings generally support the notion that hrv indices can tentatively be employed as bio-markers of top-downself-regulation. conceptual and theoretical implications, and critical gaps in current knowledge to be addressed by future work, are discussed.”
Kerr, C. E., Sacchet, M. D., Lazar, S. W., Moore, C. I., & Jones, S. R.. (2013). Mindfulness starts with the body: somatosensory attention and top-down modulation of cortical alpha rhythms in mindfulness meditation. Frontiers in Human Neuroscience
“Using a common set of mindfulness exercises, mindfulness based stress reduction (mbsr) and mindfulness based cognitive therapy (mbct) have been shown to reduce distress in chronic pain and decrease risk of depression relapse. these standardized mindfulness (st-mindfulness) practices predominantly require attending to breath and body sensations. here, we offer a novel view of st-mindfulness’s somatic focus as a form of training for optimizing attentional modulation of 7-14 hz alpha rhythms that play a key role in filtering inputs to primary sensory neocortex and organizing the flow of sensory information in the brain. in support of the framework, we describe our previous finding that st-mindfulness enhanced attentional regulation of alpha in primary somatosensory cortex (si). the framework allows us to make several predictions. in chronic pain, we predict somatic attention in st-mindfulness ‘de-biases’ alpha in si, freeing up pain-focused attentional resources. in depression relapse, we predict st-mindfulness’s somatic attention competes with internally focused rumination, as internally focused cognitive processes (including working memory) rely on alpha filtering of sensory input. our computational model predicts st-mindfulness enhances top-down modulation of alpha by facilitating precise alterations in timing and efficacy of si thalamocortical inputs. we conclude by considering how the framework aligns with buddhist teachings that mindfulness starts with ‘mindfulness of the body.’ translating this theory into neurophysiology, we hypothesize that with its somatic focus, mindfulness’ top-down alpha rhythm modulation in si enhances gain control which, in turn, sensitizes practitioners to better detect and regulate when the mind wanders from its somatic focus. this enhanced regulation of somatic mind-wandering may be an important early stage of mindfulness training that leads to enhanced cognitive regulation and metacognition.”
Wagner, D. D., Altman, M., Boswell, R. G., Kelley, W. M., & Heatherton, T. F.. (2013). Self-Regulatory Depletion Enhances Neural Responses to Rewards and Impairs Top-Down Control. Psychological Science
“To be successful at self-regulation, individuals must be able to resist impulses and desires. the strength model of self-regulation suggests that when self-regulatory capacity is depleted, self-control deficits result from a failure to engage top-down control mechanisms. using functional neuroimaging, we examined changes in brain activity in response to viewing desirable foods among 31 chronic dieters, half of whom completed a task known to result in self-regulatory depletion. compared with nondepleted dieters, depleted dieters exhibited greater food-cue-related activity in the orbitofrontal cortex, a brain area associated with coding the reward value and liking aspects of desirable foods; they also showed decreased functional connectivity between this area and the inferior frontal gyrus, a region commonly implicated in self-control. these findings suggest that self-regulatory depletion provokes self-control failure by reducing connectivity between brain regions that are involved in cognitive control and those that represent rewards, thereby decreasing the capacity to resist temptations.”
Phillips, A. G., Vacca, G., & Ahn, S.. (2008). A top-down perspective on dopamine, motivation and memory. Pharmacology Biochemistry and Behavior
“A train of action potentials (a spike train) can carry information in both the average firing rate and the pattern of spikes in the train. but can such a spike-pattern code be supported by cortical circuits? neurons in vitro produce a spike pattern in response to the injection of a fluctuating current. however, corticalneurons in vivo are modulated by local oscillatory neuronal activity and by top-down inputs. in a cortical circuit, precise spike patterns thus reflect the interaction between internally generated activity and sensory information encoded by input spike trains. we review the evidence for precise and reliable spike timing in the cortex and discuss its computational role.”