scholarly journals Neural Evidence of Statistical Learning: Efficient Detection of Visual Regularities Without Awareness

2009 ◽  
Vol 21 (10) ◽  
pp. 1934-1945 ◽  
Author(s):  
Nicholas B. Turk-Browne ◽  
Brian J. Scholl ◽  
Marvin M. Chun ◽  
Marcia K. Johnson
Keyword(s):  
Statistical Learning ◽  
Medial Temporal Lobe ◽  
Temporal Cortex ◽  
Occipital Cortex ◽  
Relational Memory ◽  
Neural Responses ◽  
Statistical Structure ◽  
Efficient Detection ◽  
Statistical Regularities ◽  
Lateral Occipital Cortex

Our environment contains regularities distributed in space and time that can be detected by way of statistical learning. This unsupervised learning occurs without intent or awareness, but little is known about how it relates to other types of learning, how it affects perceptual processing, and how quickly it can occur. Here we use fMRI during statistical learning to explore these questions. Participants viewed statistically structured versus unstructured sequences of shapes while performing a task unrelated to the structure. Robust neural responses to statistical structure were observed, and these responses were notable in four ways: First, responses to structure were observed in the striatum and medial temporal lobe, suggesting that statistical learning may be related to other forms of associative learning and relational memory. Second, statistical regularities yielded greater activation in category-specific visual regions (object-selective lateral occipital cortex and word-selective ventral occipito-temporal cortex), demonstrating that these regions are sensitive to information distributed in time. Third, evidence of learning emerged early during familiarization, showing that statistical learning can operate very quickly and with little exposure. Finally, neural signatures of learning were dissociable from subsequent explicit familiarity, suggesting that learning can occur in the absence of awareness. Overall, our findings help elucidate the underlying nature of statistical learning.

scholarly journals Changes in structural network topology correlate with severity of hallucinatory behavior in Parkinson’s disease

2019 ◽  
Vol 3 (2) ◽  
pp. 521-538 ◽  
Author(s):  
Julie M. Hall ◽  
Claire O’Callaghan ◽  
Alana J. Muller ◽  
Kaylena A. Ehgoetz Martens ◽  
Joseph R. Phillips ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Network Topology ◽  
Visual Processing ◽  
Temporal Cortex ◽  
Occipital Cortex ◽  
Structural Network ◽  
Visual Cortices ◽  
Transfer Of Information ◽  
Lateral Occipital Cortex

Inefficient integration between bottom-up visual input and higher order visual processing regions is implicated in visual hallucinations in Parkinson’s disease (PD). Here, we investigated white matter contributions to this perceptual imbalance hypothesis. Twenty-nine PD patients were assessed for hallucinatory behavior. Hallucination severity was correlated to connectivity strength of the network using the network-based statistic approach. The results showed that hallucination severity was associated with reduced connectivity within a subnetwork that included the majority of the diverse club. This network showed overall greater between-module scores compared with nodes not associated with hallucination severity. Reduced between-module connectivity in the lateral occipital cortex, insula, and pars orbitalis and decreased within-module connectivity in the prefrontal, somatosensory, and primary visual cortices were associated with hallucination severity. Conversely, hallucination severity was associated with increased between- and within-module connectivity in the orbitofrontal and temporal cortex, as well as regions comprising the dorsal attentional and default mode network. These results suggest that hallucination severity is associated with marked alterations in structural network topology with changes in participation along the perceptual hierarchy. This may result in the inefficient transfer of information that gives rise to hallucinations in PD.

scholarly journals Different Neural Responses to a Moral Valence Decision Task in Unipolar and Bipolar Depression

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Daniele Radaelli ◽  
Sara Dallaspezia ◽  
Sara Poletti ◽  
Enrico Smeraldi ◽  
Andrea Falini ◽  
...  
Keyword(s):  
Bipolar Depression ◽  
Temporal Cortex ◽  
Occipital Cortex ◽  
Anterior Cingulate ◽  
Decision Task ◽  
Neural Responses ◽  
Major Depressive ◽  
Biological Substrates ◽  
Medial Pfc ◽  
Moral Valence

Objectives. Patients affected by bipolar disorder (BP) and major depressive disorder (UP) share the susceptibility to experience depression and differ in their susceptibility to mania, but clinical studies suggest that the biological substrates of the two disorders could influence the apparently similar depressive phases. The few brain imaging studies available described different brain metabolic and neural correlates of UP and BP. Methods. We studied the BOLD neural response to a moral valence decision task targeting the depressive biases in information processing in 36 subjects (14 BP, 11 UP, and 11 controls). Results. Main differences between UP and controls and between UP and BP were detected in left ventrolateral prefrontal cortex (PFC, BA 47). Neural responses of BP patients differed from those of control subjects in multiple brain areas, including anterior cingulate cortex (ACC) and medial PFC, bilateral dorsolateral PFC, temporal cortex and insula, and parietal and occipital cortex. Conclusions. Our results are in agreement with hypotheses of dysfunctions in corticolimbic circuitries regulating affects and emotions in mood disorders and suggest that specific abnormalities, particularly in ventrolateral PFC, are not the same in UP and BP depression.

scholarly journals Statistical learning attenuates visual activity only for attended stimuli

2019 ◽  
Author(s):  
David Richter ◽  
Floris P. de Lange
Keyword(s):  
Statistical Learning ◽  
Sensory Information ◽  
Neural Responses ◽  
Visual Stream ◽  
Fmri Study ◽  
Human Volunteers ◽  
Statistical Regularities ◽  
Ventral Visual Stream ◽  
Sensory Attenuation ◽  
And Behavior

AbstractPerception and behavior can be guided by predictions, which are often based on learned statistical regularities. Neural responses to expected stimuli are frequently found to be attenuated after statistical learning. However, whether this sensory attenuation following statistical learning occurs automatically or depends on attention remains unknown. In the present fMRI study, we exposed human volunteers to sequentially presented object stimuli, in which the first object predicted the identity of the second object. We observed a strong attenuation of neural activity for expected compared to unexpected stimuli in the ventral visual stream. Crucially, this sensory attenuation was only apparent when stimuli were attended, and vanished when attention was directed away from the predictable objects. These results put important constraints on neurocomputational theories that cast perception as a process of probabilistic integration of prior knowledge and sensory information.

scholarly journals Theta-burst TMS of lateral occipital cortex reduces BOLD responses across category-selective areas in ventral temporal cortex

2020 ◽  
Author(s):  
Iris I A Groen ◽  
Edward H Silson ◽  
David Pitcher ◽  
Chris I Baker
Keyword(s):  
Temporal Cortex ◽  
Occipital Cortex ◽  
Brain Regions ◽  
Stimulus Category ◽  
Cortical Region ◽  
Face Area ◽  
Before And After ◽  
Ventral Temporal Cortex ◽  
Theta Burst ◽  
Lateral Occipital Cortex

AbstractHuman visual cortex contains three scene-selective regions in the lateral, medial and ventral cortex, termed the occipital place area (OPA), medial place area (MPA) and parahippocampal place area (PPA). Using functional magnetic resonance imaging (fMRI), all three regions respond more strongly when viewing visual scenes compared with isolated objects or faces. To determine how these regions are functionally and causally connected, we applied transcranial magnetic stimulation to OPA and measured fMRI responses before and after stimulation, using a theta-burst paradigm (TBS). To test for stimulus category-selectivity, we presented a range of visual categories (scenes, buildings, objects, faces). To test for specificity of any effects to TBS of OPA we employed two control conditions: Sham, with no TBS stimulation, and an active TBS-control with TBS to a proximal face-selective cortical region (occipital face area, or OFA). We predicted that TBS to OPA (but not OFA) would lead to decreased responses to scenes and buildings (but not other categories) in other scene-selective cortical regions. Across both ROI and whole-volume analyses, we observed decreased responses to scenes in PPA as a result of TBS. However, these effects were neither category specific, with decreased responses to all stimulus categories, nor limited to scene-selective regions, with decreases also observed in face-selective fusiform face area (FFA). Furthermore, similar effects were observed with TBS to OFA, thus effects were not specific to the stimulation site in the lateral occipital cortex. Whilst these data are suggestive of a causal, but non-specific relationship between lateral occipital and ventral temporal cortex, we discuss several factors that could have underpinned this result, such as the differences between TBS and online TMS, the role of anatomical distance between stimulated regions and how TMS effects are operationalised. Furthermore, our findings highlight the importance of active control conditions in brain stimulation experiments to accurately assess functional and causal connectivity between specific brain regions.

scholarly journals Statistical learning attenuates visual activity only for attended stimuli

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
David Richter ◽  
Floris P de Lange
Keyword(s):  
Statistical Learning ◽  
Sensory Information ◽  
Neural Responses ◽  
Visual Stream ◽  
Fmri Study ◽  
Human Volunteers ◽  
Statistical Regularities ◽  
Ventral Visual Stream ◽  
Sensory Attenuation ◽  
And Behavior

Perception and behavior can be guided by predictions, which are often based on learned statistical regularities. Neural responses to expected stimuli are frequently found to be attenuated after statistical learning. However, whether this sensory attenuation following statistical learning occurs automatically or depends on attention remains unknown. In the present fMRI study, we exposed human volunteers to sequentially presented object stimuli, in which the first object predicted the identity of the second object. We observed a reliable attenuation of neural activity for expected compared to unexpected stimuli in the ventral visual stream. Crucially, this sensory attenuation was only apparent when stimuli were attended, and vanished when attention was directed away from the predictable objects. These results put important constraints on neurocomputational theories that cast perception as a process of probabilistic integration of prior knowledge and sensory information.

scholarly journals Neural Responses to Central and Peripheral Objects in the Lateral Occipital Cortex

2016 ◽  
Vol 10 ◽  
Author(s):  
Bin Wang ◽  
Jiayue Guo ◽  
Tianyi Yan ◽  
Seiichiro Ohno ◽  
Susumu Kanazawa ◽  
...  
Keyword(s):  
Occipital Cortex ◽  
Neural Responses ◽  
Lateral Occipital Cortex

Prior real-world experience influences non-linguistic statistical learning

2020 ◽  
Author(s):  
Stephen Charles Van Hedger ◽  
Ingrid Johnsrude ◽  
Laura Batterink
Keyword(s):  
Statistical Learning ◽  
Real World ◽  
Language Experience ◽  
Pitch Range ◽  
Test Items ◽  
Instrument Measuring ◽  
Statistical Regularities ◽  
Context Free ◽  
Specific Learning

Listeners are adept at extracting regularities from the environment, a process known as statistical learning (SL). SL has been generally assumed to be a form of “context-free” learning that occurs independently of prior knowledge, and SL experiments typically involve exposing participants to presumed novel regularities, such as repeating nonsense words. However, recent work has called this assumption into question, demonstrating that learners’ previous language experience can considerably influence SL performance. In the present experiment, we tested whether previous knowledge also shapes SL in a non-linguistic domain, using a paradigm that involves extracting regularities over tone sequences. Participants learned novel tone sequences, which consisted of pitch intervals not typically found in Western music. For one group of participants, the tone sequences used artificial, computerized instrument sounds. For the other group, the same tone sequences used familiar instrument sounds (piano or violin). Knowledge of the statistical regularities was assessed using both trained sounds (measuring specific learning) and sounds that differed in pitch range and/or instrument (measuring transfer learning). In a follow-up experiment, two additional testing sessions were administered to gauge retention of learning (one day and approximately one-week post-training). Compared to artificial instruments, training on sequences played by familiar instruments resulted in reduced correlations among test items, reflecting more idiosyncratic performance. Across all three testing sessions, learning of novel regularities presented with familiar instruments was worse compared to unfamiliar instruments, suggesting that prior exposure to music produced by familiar instruments interfered with new sequence learning. Overall, these results demonstrate that real-world experience influences SL in a non-linguistic domain, supporting the view that SL involves the continuous updating of existing representations, rather than the establishment of entirely novel ones.

scholarly journals Dysfunctions in Infants’ Statistical Learning are Related to Parental Autistic Traits

2021 ◽  
Author(s):  
Bettoni Roberta ◽  
Valentina Riva ◽  
Chiara Cantiani ◽  
Elena Maria Riboldi ◽  
Massimo Molteni ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Skills ◽  
Statistical Learning ◽  
Crucial Role ◽  
Autistic Traits ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Statistical Structure ◽  
The Relationship ◽  
Visual Habituation

AbstractStatistical learning refers to the ability to extract the statistical relations embedded in a sequence, and it plays a crucial role in the development of communicative and social skills that are impacted in the Autism Spectrum Disorder (ASD). Here, we investigated the relationship between infants’ SL ability and autistic traits in their parents. Using a visual habituation task, we tested infant offspring of adults (non-diagnosed) who show high (HAT infants) versus low (LAT infants) autistic traits. Results demonstrated that LAT infants learned the statistical structure embedded in a visual sequence, while HAT infants failed. Moreover, infants’ SL ability was related to autistic traits in their parents, further suggesting that early dysfunctions in SL might contribute to variabilities in ASD symptoms.

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