RESUMEN
Physical exercise is considered a promising medication-free and cost-effective adjunct treatment for substance use disorders (SUD). Nevertheless, evidence regarding the effectiveness of these interventions is currently limited, thereby signaling the need to better understand the mechanisms underlying their impact on SUD, in order to reframe and optimize them. Here we advance that physical exercise could be re-conceptualized as an "interoception booster", namely as a way to help people with SUD to better decode and interpret bodily-related signals associated with transient states of homeostatic imbalances that usually trigger consumption. We first discuss how mismatches between current and desired bodily states influence the formation of reward-seeking states in SUD, in light of the insular cortex brain networks. Next, we detail effort perception during physical exercise and discuss how it can be used as a relevant framework for re-dynamizing interoception in SUD. We conclude by providing perspectives and methodological considerations for applying the proposed approach to mixed-design neurocognitive research on SUD.
Asunto(s)
Interocepción , Trastornos Relacionados con Sustancias , Humanos , Trastornos Relacionados con Sustancias/terapia , Encéfalo , Ejercicio FísicoRESUMEN
PURPOSE: The purposes of this study were to (a) investigate the effect of physical effort (cycling for 60 min at 60 ± 5% of individually computed reserve heart-rate capacity), combined with 2 different levels of cognitive demand (2-back, oddball), on intraocular pressure (IOP) and subjective judgments of perceived exertion (ratings of perceived exertion [RPE]), affect (Affective Valence subscale of the Self-Assessment Manikin [SAM]), and mental workload (National Aeronautics and Space Administration Task Load Index [NASA-TLX]); and (b) ascertain whether baseline IOP, measured before exercise, is associated with individual differences in subjective assessments of effort and affective response during exercise. METHOD: Seventeen participants (Mage = 23.28 ± 2.37 years) performed 2 physical/cognitive dual tasks, matched in physical demand but with different mental requirements (2-back, oddball). We assessed IOP before exercise, after 2 min of active recovery, and after 15 min of passive recovery, and we also collected RPE and SAM measures during the sessions (28 measurement points). We used NASA-TLX and cognitive performance as checks of the mental manipulation. RESULTS: (a) Intraocular pressure increased after concomitant physical/mental effort, with the effect reaching statistical significance after the 2-back task (p = .002, d = 0.35) but not after the oddball condition (p = .092, d = 0.29). (b) Baseline IOP was associated with subjective sensitivity to effort and showed statistical significance for the oddball condition (p = .03, Æp2 = .622) but not for the 2-back task (F < 1). CONCLUSIONS: Results suggest a relationship between IOP and physical/cognitive effort, which could have implications for the management of glaucoma. Additionally, a rapid measure of IOP could be used as a marker of individual effort sensitivity in applied settings.
Asunto(s)
Cognición , Ejercicio Físico/psicología , Presión Intraocular , Esfuerzo Físico , Carga de Trabajo/psicología , Adulto , Frecuencia Cardíaca , Humanos , Masculino , Memoria a Corto Plazo , Adulto JovenRESUMEN
RATIONALE: Research on the relative impact of trait impulsivity vs. drug exposure on neuropsychological probes of response inhibition vs. response perseveration has been posited as a valid pathway to explore the transition between impulsivity and compulsivity on psychostimulant dependence. OBJECTIVES: The objectives of this study are to examine performance differences between cocaine-dependent individuals (CDI) and healthy comparison individuals (HCI) on neuropsychological probes of inhibition and perseveration and to examine the predictive impact of trait impulsivity-a proxy of premorbid vulnerability, and severity of cocaine use-a proxy of drug exposure, on CDI's performance. METHODS: Forty-two CDI and 65 HCI were assessed using the UPPS-P Scale (trait impulsivity), the Stroop and go/no-go (inhibition) and revised-strategy application and probabilistic reversal tests (perseveration). RESULTS: CDI, compared to HCI, have elevated scores on trait impulsivity and perform significantly poorer on inhibition and perseveration, with specific detrimental effects of duration of cocaine use on perseveration. CONCLUSIONS: CDI have both inhibition and perseveration deficits; both patterns were broadly indicative of orbitofrontal dysfunction in the context of reinforcement learning. Impulsive personality and cocaine exposure jointly contribute to deficits in response perseveration or compulsivity.
Asunto(s)
Trastornos Relacionados con Cocaína/psicología , Conducta Compulsiva/psicología , Conducta Impulsiva/psicología , Pruebas Neuropsicológicas/estadística & datos numéricos , Adulto , Estudios de Casos y Controles , Trastornos Relacionados con Cocaína/complicaciones , Trastornos Relacionados con Cocaína/diagnóstico , Humanos , Conducta Impulsiva/complicaciones , Inhibición Psicológica , Masculino , Desempeño PsicomotorRESUMEN
The main aim of this work was to look for cognitive biases in human inference of causal relationships in order to emphasize the psychological processes that modulate causal learning. From the effect of the judgment frequency, this work presents subsequent research on cue competition (overshadowing, blocking, and super-conditioning effects) showing that the strength of prior beliefs and new evidence based upon covariation computation contributes additively to predict causal judgments, whereas the balance between the reliability of both, beliefs and covariation knowledge, modulates their relative weight. New findings also showed "inattentional blindness" for negative or preventative causal relationships but not for positive or generative ones, due to failure in codifying and retrieving the necessary information for its computation. Overall results unveil the need of three hierarchical levels of a whole architecture for human causal learning: the lower one, responsible for codifying the events during the task; the second one, computing the retrieved information; finally, the higher level, integrating this evidence with previous causal knowledge. In summary, whereas current theoretical frameworks on causal inference and decision-making usually focused either on causal beliefs or covariation information, the present work shows how both are required to be able to explain the complexity and flexibility involved in human causal learning.