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![The hippocampus, dentate gyrus and fimbria as they appear after removal of the roof of the temporal horn of the lateral ventricle and of the choroid plexus (modified from Piersol, 1928 [27]). The photograph on the right (courtesy of Dr. Laszlo Seriss, University of Pecs, Hungary) shows a dissected hippocampal formation, including the reflexed intrauncal component, with a sea-horse alongside.](profile/John-Kiernan/publication/230763946/figure/fig3/AS:202825796722695@1425368846861/The-hippocampus-dentate-gyrus-and-fimbria-as-they-appear-after-removal-of-the-roof-of.png)
The hippocampus, dentate gyrus and fimbria as they appear after removal of the roof of the temporal horn of the lateral ventricle and of the choroid plexus (modified from Piersol, 1928 [27]). The photograph on the right (courtesy of Dr. Laszlo Seriss, University of Pecs, Hungary) shows a dissected hippocampal formation, including the reflexed intrauncal component, with a sea-horse alongside.
Source publication
Only primates have temporal lobes, which are largest in man, accommodating 17% of the cerebral cortex and including areas with auditory, olfactory, vestibular, visual and linguistic functions. The hippocampal formation, on the medial side of the lobe, includes the parahippocampal gyrus, subiculum, hippocampus, dentate gyrus, and associated white ma...
Citations
... Surprisingly, we also had the results of 23 voxels on three BAs (BA21, BA22, and BA42) on the temporal lobe, which are not commonly found in the results of the alpha frequency band. The potential reason for these findings could be related to the experimental task design, in which participants were required to read the semantic stimuli out aloud, and the temporal lobe is known for its association with auditory, visual, and linguistic processing [44]. ...
This study employed electroencephalogram (EEG) to collect brain activity while participants read different kinds of semantic stimuli. The standardized low-resolution brain electromagnetic tomography method was used to analyze the current source in both the lower alpha frequency band (8-10 Hz) and the upper alpha frequency band (10-13 Hz). This study focused on understanding how semantic stimuli with different degrees of abstraction influence design creativity and on exploring the activities of the brain when processing them. The results showed abstract stimuli evoked a larger current source in the upper alpha frequency band compared to concrete stimuli on 269 voxels distributed in 13 Brodmann areas and among three lobes (frontal, temporal, and occipital). Additionally, there was a positive correlation between the upper alpha current source and both novelty scores and surprise scores. These results substantiate the hypothesis that activities in the upper alpha band are conducive to enhancing design creativity. 2 M. Wang et al.
... The olfactory tract extends from the olfactory bulb along the base of the frontal cortex [20], and the target of SARS-CoV-2 virus, angiotensin-converting enzyme 2, is commonly expressed in vessels of various calibers in the frontal cortex [21]. Extensive connectivity exists between the occipital lobe and the olfactory bulb [22], and the amygdala, located in the medial part of the temporal lobe, receives inputs from the olfactory bulb and the associated cortex [23]. During viral brain infections, microglia and infiltrating macrophages secrete various inflammatory factors aimed at viral clearance. ...
Background
To evaluate the neurological alterations induced by Omicron infection, to compare brain changes in chronic insomnia with those in exacerbated chronic insomnia in Omicron patients, and to examine individuals without insomnia alongside those with new-onset insomnia.
Methods
In this study, a total of 135 participants were recruited between January 11 and May 4, 2023, including 26 patients with chronic insomnia without exacerbation, 24 patients with chronic insomnia with exacerbation, 40 patients with no sleep disorder, and 30 patients with new-onset insomnia after infection with Omicron (a total of 120 participants with different sleep statuses after infection), as well as 15 healthy controls who were never infected with Omicron. Neuropsychiatric data, clinical symptoms, and multimodal magnetic resonance imaging data were collected. The gray matter thickness and T1, T2, proton density, and perivascular space values were analyzed. Associations between changes in multimodal magnetic resonance imaging findings and neuropsychiatric data were evaluated with correlation analyses.
Results
Compared with healthy controls, gray matter thickness changes were similar in the patients who have and do not have a history of chronic insomnia groups after infection, including an increase in cortical thickness near the parietal lobe and a reduction in cortical thickness in the frontal, occipital, and medial brain regions. Analyses showed a reduced gray matter thickness in patients with chronic insomnia compared with those with an aggravation of chronic insomnia post-Omicron infection, and a reduction was found in the right medial orbitofrontal region (mean [SD], 2.38 [0.17] vs. 2.67 [0.29] mm; P < 0.001). In the subgroups of Omicron patients experiencing sleep deterioration, patients with a history of chronic insomnia whose insomnia symptoms worsened after infection displayed heightened medial orbitofrontal cortical thickness and increased proton density values in various brain regions. Conversely, patients with good sleep quality who experienced a new onset of insomnia after infection exhibited reduced cortical thickness in pericalcarine regions and decreased proton density values. In new-onset insomnia patients post-Omicron infection, the thickness in the right pericalcarine was negatively correlated with the Self-rating Anxiety Scale (r = − 0.538, P = 0.002, PFDR = 0.004) and Self-rating Depression Scale (r = − 0.406, P = 0.026, PFDR = 0.026) scores.
Conclusions
These findings help us understand the pathophysiological mechanisms involved when Omicron invades the nervous system and induces various forms of insomnia after infection. In the future, we will continue to pay attention to the dynamic changes in the brain related to insomnia caused by Omicron infection.
... The temporal cortex maintains connections through association fibers to all forebrain lobes. 31 Likewise, the deep GM, especially the thalamus, shows extensive projections to the cerebral cortex. Additionally, the insula features an intricate network of connections with both cortical and subcortical structures. ...
Objective
To evaluate: (1) the distribution of gray matter (GM) atrophy in myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD), aquaporin‐4 antibody‐positive neuromyelitis optica spectrum disorder (AQP4+NMOSD), and relapsing–remitting multiple sclerosis (RRMS); and (2) the relationship between GM volumes and white matter lesions in various brain regions within each disease.
Methods
A retrospective, multicenter analysis of magnetic resonance imaging data included patients with MOGAD/AQP4+NMOSD/RRMS in non‐acute disease stage. Voxel‐wise analyses and general linear models were used to evaluate the relevance of regional GM atrophy. For significant results ( p < 0.05), volumes of atrophic areas are reported.
Results
We studied 135 MOGAD patients, 135 AQP4+NMOSD, 175 RRMS, and 144 healthy controls (HC). Compared with HC, MOGAD showed lower GM volumes in the temporal lobes, deep GM, insula, and cingulate cortex (75.79 cm ³ ); AQP4+NMOSD in the occipital cortex (32.83 cm ³ ); and RRMS diffusely in the GM (260.61 cm ³ ). MOGAD showed more pronounced temporal cortex atrophy than RRMS (6.71 cm ³ ), whereas AQP4+NMOSD displayed greater occipital cortex atrophy than RRMS (19.82 cm ³ ). RRMS demonstrated more pronounced deep GM atrophy in comparison with MOGAD (27.90 cm ³ ) and AQP4+NMOSD (47.04 cm ³ ). In MOGAD, higher periventricular and cortical/juxtacortical lesions were linked to reduced temporal cortex, deep GM, and insula volumes. In RRMS, the diffuse GM atrophy was associated with lesions in all locations. AQP4+NMOSD showed no lesion/GM volume correlation.
Interpretation
GM atrophy is more widespread in RRMS compared with the other two conditions. MOGAD primarily affects the temporal cortex, whereas AQP4+NMOSD mainly involves the occipital cortex. In MOGAD and RRMS, lesion‐related tract degeneration is associated with atrophy, but this link is absent in AQP4+NMOSD. ANN NEUROL 2024
... The amygdala, a complex neural structure, comprises two primary components: the medial and basolateral amygdala, situated within the depths of the temporal lobe (Kiernan 2012). It is known as the center of emotional learning and behavior, including fear, anxiety, and aggression, as well as behavioral reactions such as freezing and facemask expression of fear (Amunts et al. 2005;Buchanan et al. 2003). ...
While breathing is a vital, involuntary physiological function, the mode of respiration, particularly nasal breathing, exerts a profound influence on brain activity and cognitive processes. This review synthesizes existing research on the interactions between nasal respiration and the entrainment of oscillations across brain regions involved in cognition. The rhythmic activation of olfactory sensory neurons during nasal respiration is linked to oscillations in widespread brain regions, including the prefrontal cortex, entorhinal cortex, hippocampus, amygdala, and parietal cortex, as well as the piriform cortex. The phase-locking of neural oscillations to the respiratory cycle, through nasal breathing, enhances brain inter-regional communication and is associated with cognitive abilities like memory. Understanding the nasal breathing impact on brain networks offers opportunities to explore novel methods for targeting the olfactory pathway as a means to enhance emotional and cognitive functions.
... HG divides the superior temporal surface into three parts, with planum polare and planum temporale (PT), anterior and posterior to HG, respectively. The terminology is variable, sometimes gyri on the superior temporal surface are called TTG and the term HG is reserved for only the most posterior TTG bounded posteriorly by the deep transverse temporal sulcus (Kiernan, 2012, Naidich et al., 2001. Sometimes anterior PT is included with TTG/HG and posterior part of PT along the ascending ramus of the sylvian fissure is considered anatomically distinct (Kiernan, 2012, Naidich et al., 2001. ...
... The terminology is variable, sometimes gyri on the superior temporal surface are called TTG and the term HG is reserved for only the most posterior TTG bounded posteriorly by the deep transverse temporal sulcus (Kiernan, 2012, Naidich et al., 2001. Sometimes anterior PT is included with TTG/HG and posterior part of PT along the ascending ramus of the sylvian fissure is considered anatomically distinct (Kiernan, 2012, Naidich et al., 2001. Also, functionally PT may consist of two distinct zones, including an anterior auditory-related zone and a posterior auditory-motor zone (Hickok et al., 2009, Isenberg et al., 2012. ...
... Therefore, there is multimodal evidence for involvement of TTG+, posterior STG, and STS in emotional aspects of communication. Notably, STS, STG, and TTG+ share contiguous and immediately adjacent neocortex (Kiernan, 2012), and we have shown TTG+ to have high restingstate connectivity with STG for both language (first-degree) and motor (second-degree) sites (Fig. 4). Therefore, we speculate that TTG+, which is a component of primary auditory cortex, may be under modulatory control of STS and posterior STG, and participates in responding to emotional cues through facial expressions. ...
... What the author misses out, probably because his book was published in 1996, is that hippocampus, which is in the limbic system at the temporal lobe is associated with the formation of implicit and explicit memories, as well as episodic and declarative ones (comp. Kiernan, 2012;Science Direct Editorial, 2018); in PTSD cases, should them haven't been treated for 20 years and over that, its dendrites or dendritic spines appear virtually inexistent or severely decreased: dendrites and/or dendritic spines relate to psychopathological correlates (comp. Penzes et al., 2011). ...
Since the publication of Goleman's book, in 1996, there has been an explosion in the use of his arguments that emotions are those which really generate cognitions and not the other way around. According to a layman's point of view, people who feel certain emotions, they then think how to execute them. To use one of the main emotions, the author speaks about in most pages of his book, is that of anger: anger is a very strong emotion; one may become passive-aggressive; another may employ it as a response to a real or hypothetical external threat. As a process-using an emotion to generate thinking-seems and sounds to be correct, and primarily I would agree to that, however does that mean that this is the only scientific/methodological answer? This paper is a review on Goleman's argument and attempts to present conceptual shortcomings which haven't been taken into consideration when the author was presenting his argument. In this review, the order we follow to outline our counterargument to emotional intelligence are the cognitive and behavioural ABC (activating event-beliefs-consequences) models in the relationship between a trigger, a thought pattern, an emotional presentation, and a behavioural reaction, according to the CBT (cognitive-behavioural therapy) perspective. In this paper, there will also be offered connections between the emotional intelligence argument and a writing by Voltaire, a writing by Schwab & Maleret, a writing by Soros, and a writing by Bock-Côté. In the latter author, there will be finally offered some juxtapositions in line with the paradigm of psychology of religion. Keywords: emotional intelligence, cognitive intelligence, emotions, cognitive-behavioural therapy (CBT), conceptual shortcomings, psychology of religion. Prolegomena This book is all about emotions and the intelligence they present/exhibit against the importance of the intelligence of cognitions. The main argument of the author is that cognitions are derivatives of emotions. According to the author, intelligence resides only within emotions, whereas cognitions are patterns of expression and not genuine characteristics of the faculties of the brain. In this review, I present and discuss counterarguments drawn from the cognitive-behavioural therapy modality that cognitions can have what we call intelligence which generates specific emotional reactivity and it is not that cognitions are by-products of emotions. The author what also includes in his presentation of emotions are also instincts and aggression deriving from them, which he considers them as of prime importance when discusses anger. In his book the author uses neuroscientific considerations about emotions which have as their basis the area of amygdala in the brain. The author's axis in presenting his case of emotional intelligence rests upon the following pillars: 1. Amygdala. 2. Anger as the main emotion which governs human life-this is what appears in the book based on examples the author uses and explanations he provides afterwards. 3. EQ (emotional quotient) instead of IQ (intelligence quotient).
... The basal temporal surface is traversed longitudinally by 3 sulci that divide it into the inferior temporal gyrus (ITG), the fusiform gyrus (FG, also known as gyrus occipitotemporalis lateralis), and the parahippocampal gyrus (PhG). 8,9 Parahippocampal ramus (Phr) separates the PhG from the lingual gyrus (LG) and constitutes a supplementary branch of the CoS. Laterally, the temporal lobe is limited superiorly by the Sylvian fissure and separated by the superior temporal sulcus (STS) and inferior temporal sulcus (ITS) temporal sulci, which are parallel to each other. ...
... Laterally, the temporal lobe is limited superiorly by the Sylvian fissure and separated by the superior temporal sulcus (STS) and inferior temporal sulcus (ITS) temporal sulci, which are parallel to each other. 5,[8][9][10][11][12] The ITG is often separated into small parts by 1 or more sulcal bridges and can merge into the MTG with no apparent boundary. 5,8,10,11 The temporal lobe is separated by these sulci laterally into the superior temporal gyrus, middle temporal gyrus (MTG), and ITG, and these gyri are respectively known as T1, T2, and T3. ...
... Inferiorly, the ITG folds from the convexity around the inferolateral margin of the basal hemispheric surface. 6,8,9,11 The border between the temporal and occipital lobes at the inferior aspect of the brain is described in various ways in recent neuroanatomical textbooks. This study aimed to define the boundaries of the temporal and occipital lobes anatomically and to define the variations in sulci and gyri in the inferior aspect. ...
... The olfactory tract extends from the olfactory bulb along the base of the frontal cortex 20 , and the target of SARS-CoV-2 virus, angiotensin converting enzyme 2 (ACE2), is commonly expressed in vessels of various calibers in the frontal cortex 21 . Extensive connectivity exists between the occipital lobe and the olfactory bulb 22 , and the amygdala, located in the medial part of the temporal lobe, receives inputs from the olfactory bulb and the associated cortex 23 . During viral brain infections, microglia and in ltrating macrophages secrete various in ammatory factors aimed at viral clearance. ...
IMPORTANCE Whether the mechanism of nervous system invasion and the brain regions targeted by the currently prevalent Omicron strain parallel those of the Delta strain is unclear. Insomnia is a prevalent and persistent issue following Delta variant infection, yet our comprehension of the connection between Omicron strains and insomnia remains limited.
OBJECTIVE To evaluate the neurological alterations induced by Omicron infection, to compare brain changes in chronic insomnia with those in exacerbated chronic insomnia in Omicron patients and to examine individuals without insomnia alongside those with new-onset insomnia.
DESIGN, SETTING, AND PARTICIPANTS In this cohort study, a total of 135 participants were recruited between January 11 and May 4, 2023, including 120 participants with different sleep statuses after infection with Omicron and 15 healthy controls. Neuropsychiatric data, clinical symptoms, and multimodal magnetic resonance imaging data were collected. The gray matter thickness and T1, T2, proton density, and perivascular space values were analyzed. Associations between changes in multimodal magnetic resonance imaging findings and neuropsychiatric data were evaluated with correlation analyses.
EXPOSURES Gray matter thickness was evaluated based on the neurological alterations induced by Omicron infection, and multimodal magnetic resonance imaging was used to explore the effects of Omicron infections on sleep patterns in various populations.
MAIN OUTCOMES AND MEASURES
Neuropsychiatric scale scores were evaluated by using IBM SPSS Statistics 24.0. Gray matter thickness and T1, T2, proton density, and perivascular space values were calculated from three-dimensional magnetization-prepared rapid acquisition gradient echo, magnetic resonance image compilation and diffusion tensor imaging sequences, respectively, using image data analysis software.
RESULTS
Compared with healthy controls, patients with chronic insomnia, aggravation of chronic insomnia, and new-onset insomnia had significantly higher Self-rating Anxiety Scale and Self-rating Depression Scale scores post-Omicron infection. Compared with healthy controls, the gray matter thickness was significantly reduced in the left medial orbitofrontal, lingual, pericalcarine and right lateral occipital lobes and significantly increased in the left inferior parietal and right superior parietal lobes in the patients with chronic insomnia post-Omicron infection. The individuals with good sleep quality had no change in sleep status after infection; significantly reduced gray matter thickness of the left medial orbitofrontal, cuneus, lingual and right pericalcarine; and increased gray matter thickness in the left inferior parietal, supramarginal, and bilateral superior parietal regions compared with healthy controls. Analyses showed a reduced gray matter thickness in patients with chronic insomnia compared with those with an aggravation of chronic insomnia post-Omicron infection, and a reduction was found in the right medial orbitofrontal region (mean [SD], 2.38 [0.17] vs. 2.67 [0.29] mm; P < 0.001). Compared with patients with chronic insomnia, patients with an aggravation of chronic insomnia post-Omicron infection showed a significant decrease in T1 values (left occipital and right olfactory and temporal lobes) and an increase in T2 values (left occipital and parietal and right precuneus lobes) and proton density values (bilateral frontal and right occipital and precuneus lobes). New-onset insomnia patients showed reduced gray matter thickness in the right pericalcarine (mean [SD], 1.62 [0.16] vs. 1.50 [0.15] mm; P < 0.001), and they had significantly decreased proton density values (right lingual, fusiform, parietal and temporal lobes) compared to individuals with good sleep quality, who showed no change in sleep status after infection. In new-onset insomnia patients post-Omicron infection, the thickness in the right pericalcarine was negatively correlated with the Self-rating Anxiety Scale (r = -0.538, P = 0.002, PFDR = 0.004) and Self-rating Depression Scale (r = -0.406, P = 0.026, PFDR = 0.026) scores.
CONCLUSIONS AND RELEVANCE
In summary, changes in gray matter thickness after Omicron infection were similar in chronic insomnia patients and healthy people, but there were significant differences in gray matter thickness and T1, T2, and proton density values in patients with different sleep qualities. These findings help us understand the pathophysiological mechanisms involved when Omicron invade the nervous system and induce various forms of insomnia after infection. In the future, we will continue to pay attention to the dynamic changes in the brain related to insomnia caused by Omicron infection.
... These regions, including the supramarginal gyrus and angular gyrus, are traditionally known as sensory-motor integration areas, and process and relay afferent information to generate movement planning [97]. The temporal lobe was found to have a rich connection with the frontal lobe, occipital lobe, and thalamus, suggestive of its potentially integrative role for these regions [98]. ...
Swallowing is a sophisticated process involving the precise and timely coordination of the central and peripheral nervous systems, along with the musculatures of the oral cavity, pharynx, and airway. The role of the infratentorial neural structure, including the swallowing central pattern generator and cranial nerve nuclei, has been described in greater detail compared with both the cortical and subcortical neural structures. Nonetheless, accumulated data from analysis of swallowing performance in patients with different neurological diseases and conditions, along with results from neurophysiological studies of normal swallowing have gradually enhanced understanding of the role of cortical and subcortical neural structures in swallowing, potentially leading to the development of treatment modalities for patients suffering from dysphagia. This review article summarizes findings about the role of both cortical and subcortical neural structures in swallowing based on results from neurophysiological studies and studies of various neurological diseases. In sum, cortical regions are mainly in charge of initiation and coordination of swallowing after receiving afferent information, while subcortical structures including basal ganglia and thalamus are responsible for movement control and regulation during swallowing through the cortico-basal ganglia-thalamo-cortical loop. This article also presents how cortical and subcortical neural structures interact with each other to generate the swallowing response. In addition, we provided the updated evidence about the clinical applications and efficacy of neuromodulation techniques, including both non-invasive brain stimulation and deep brain stimulation on dysphagia.
... In conclusion, (1) cognitive decline due to alterations in the left temporal region and/or in specific hippocampal subfields may be characteristic of MSA-MCI, atrophy of the middle temporal gyrus probably representing the main cause of cognitive decline in MSA. It should be emphasized that the left temporal lobe is involved in many cognitive processes, including visual processing and delayed memory (inferior temporal gyrus) (Ju et al. 2020;Kiernan 2012;Kuroki et al. 2006), and language processing and semantic comprehension (superior temporal gyrus) (Fan et al. 2017;Kiehl et al. 2004;Wei et al. 2012). ...
Cognitive impairment (CI), previously considered as a non-supporting feature of multiple system atrophy (MSA), according to the second consensus criteria, is not uncommon in this neurodegenerative disorder that is clinically characterized by a variable combination of autonomic failure, levodopa-unresponsive parkinsonism, motor and cerebellar signs. Mild cognitive impairment (MCI), a risk factor for dementia, has been reported in up to 44% of MSA patients, with predominant impairment of executive functions/attention, visuospatial and verbal deficits, and a variety of non-cognitive and neuropsychiatric symptoms. Despite changing concept of CI in this synucleinopathy, the underlying pathophysiological mechanisms remain controversial. Recent neuroimaging studies revealed volume reduction in the left temporal gyrus, and in the dopaminergic nucleus accumbens, while other morphometric studies did not find any gray matter atrophy, in particular in the frontal cortex. Functional analyses detected decreased functional connectivity in the left parietal lobe, bilateral cuneus, left precuneus, limbic structures, and cerebello-cerebral circuit, suggesting that structural and functional changes in the subcortical limbic structures and disrupted cerebello-cerebral networks may be associated with early cognitive decline in MSA. Whereas moderate to severe CI in MSA in addition to prefrontal-striatal degeneration is frequently associated with cortical Alzheimer and Lewy co-pathologies, neuropathological studies of the MCI stage of MSA are unfortunately not available. In view of the limited structural and functional findings in MSA cases with MCI, further neuroimaging and neuropathological studies are warranted in order to better elucidate its pathophysiological mechanisms and to develop validated biomarkers as basis for early diagnosis and future adequate treatment modalities in order to prevent progression of this debilitating disorder.
